---
_id: '13352'
abstract:
- lang: eng
text: Optoelectronic effects differentiating absorption of right and left circularly
polarized photons in thin films of chiral materials are typically prohibitively
small for their direct photocurrent observation. Chiral metasurfaces increase
the electronic sensitivity to circular polarization, but their out-of-plane architecture
entails manufacturing and performance trade-offs. Here, we show that nanoporous
thin films of chiral nanoparticles enable high sensitivity to circular polarization
due to light-induced polarization-dependent ion accumulation at nanoparticle interfaces.
Self-assembled multilayers of gold nanoparticles modified with L-phenylalanine
generate a photocurrent under right-handed circularly polarized light as high
as 2.41 times higher than under left-handed circularly polarized light. The strong
plasmonic coupling between the multiple nanoparticles producing planar chiroplasmonic
modes facilitates the ejection of electrons, whose entrapment at the membrane–electrolyte
interface is promoted by a thick layer of enantiopure phenylalanine. Demonstrated
detection of light ellipticity with equal sensitivity at all incident angles mimics
phenomenological aspects of polarization vision in marine animals. The simplicity
of self-assembly and sensitivity of polarization detection found in optoionic
membranes opens the door to a family of miniaturized fluidic devices for chiral
photonics.
article_processing_charge: No
article_type: original
author:
- first_name: Jiarong
full_name: Cai, Jiarong
last_name: Cai
- first_name: Wei
full_name: Zhang, Wei
last_name: Zhang
- first_name: Liguang
full_name: Xu, Liguang
last_name: Xu
- first_name: Changlong
full_name: Hao, Changlong
last_name: Hao
- first_name: Wei
full_name: Ma, Wei
last_name: Ma
- first_name: Maozhong
full_name: Sun, Maozhong
last_name: Sun
- first_name: Xiaoling
full_name: Wu, Xiaoling
last_name: Wu
- first_name: Xian
full_name: Qin, Xian
last_name: Qin
- first_name: Felippe Mariano
full_name: Colombari, Felippe Mariano
last_name: Colombari
- first_name: André Farias
full_name: de Moura, André Farias
last_name: de Moura
- first_name: Jiahui
full_name: Xu, Jiahui
last_name: Xu
- first_name: Mariana Cristina
full_name: Silva, Mariana Cristina
last_name: Silva
- first_name: Evaldo Batista
full_name: Carneiro-Neto, Evaldo Batista
last_name: Carneiro-Neto
- first_name: Weverson Rodrigues
full_name: Gomes, Weverson Rodrigues
last_name: Gomes
- first_name: Renaud A. L.
full_name: Vallée, Renaud A. L.
last_name: Vallée
- first_name: Ernesto Chaves
full_name: Pereira, Ernesto Chaves
last_name: Pereira
- first_name: Xiaogang
full_name: Liu, Xiaogang
last_name: Liu
- first_name: Chuanlai
full_name: Xu, Chuanlai
last_name: Xu
- first_name: Rafal
full_name: Klajn, Rafal
id: 8e84690e-1e48-11ed-a02b-a1e6fb8bb53b
last_name: Klajn
- first_name: Nicholas A.
full_name: Kotov, Nicholas A.
last_name: Kotov
- first_name: Hua
full_name: Kuang, Hua
last_name: Kuang
citation:
ama: Cai J, Zhang W, Xu L, et al. Polarization-sensitive optoionic membranes from
chiral plasmonic nanoparticles. Nature Nanotechnology. 2022;17(4):408-416.
doi:10.1038/s41565-022-01079-3
apa: Cai, J., Zhang, W., Xu, L., Hao, C., Ma, W., Sun, M., … Kuang, H. (2022). Polarization-sensitive
optoionic membranes from chiral plasmonic nanoparticles. Nature Nanotechnology.
Springer Nature. https://doi.org/10.1038/s41565-022-01079-3
chicago: Cai, Jiarong, Wei Zhang, Liguang Xu, Changlong Hao, Wei Ma, Maozhong Sun,
Xiaoling Wu, et al. “Polarization-Sensitive Optoionic Membranes from Chiral Plasmonic
Nanoparticles.” Nature Nanotechnology. Springer Nature, 2022. https://doi.org/10.1038/s41565-022-01079-3.
ieee: J. Cai et al., “Polarization-sensitive optoionic membranes from chiral
plasmonic nanoparticles,” Nature Nanotechnology, vol. 17, no. 4. Springer
Nature, pp. 408–416, 2022.
ista: Cai J, Zhang W, Xu L, Hao C, Ma W, Sun M, Wu X, Qin X, Colombari FM, de Moura
AF, Xu J, Silva MC, Carneiro-Neto EB, Gomes WR, Vallée RAL, Pereira EC, Liu X,
Xu C, Klajn R, Kotov NA, Kuang H. 2022. Polarization-sensitive optoionic membranes
from chiral plasmonic nanoparticles. Nature Nanotechnology. 17(4), 408–416.
mla: Cai, Jiarong, et al. “Polarization-Sensitive Optoionic Membranes from Chiral
Plasmonic Nanoparticles.” Nature Nanotechnology, vol. 17, no. 4, Springer
Nature, 2022, pp. 408–16, doi:10.1038/s41565-022-01079-3.
short: J. Cai, W. Zhang, L. Xu, C. Hao, W. Ma, M. Sun, X. Wu, X. Qin, F.M. Colombari,
A.F. de Moura, J. Xu, M.C. Silva, E.B. Carneiro-Neto, W.R. Gomes, R.A.L. Vallée,
E.C. Pereira, X. Liu, C. Xu, R. Klajn, N.A. Kotov, H. Kuang, Nature Nanotechnology
17 (2022) 408–416.
date_created: 2023-08-01T09:32:40Z
date_published: 2022-03-14T00:00:00Z
date_updated: 2023-08-02T09:44:31Z
day: '14'
doi: 10.1038/s41565-022-01079-3
extern: '1'
external_id:
pmid:
- '35288671'
intvolume: ' 17'
issue: '4'
keyword:
- Electrical and Electronic Engineering
- Condensed Matter Physics
- General Materials Science
- Biomedical Engineering
- Atomic and Molecular Physics
- and Optics
- Bioengineering
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://hal.science/hal-03623036/
month: '03'
oa: 1
oa_version: Published Version
page: 408-416
pmid: 1
publication: Nature Nanotechnology
publication_identifier:
eissn:
- 1748-3395
issn:
- 1748-3387
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Polarization-sensitive optoionic membranes from chiral plasmonic nanoparticles
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 17
year: '2022'
...
---
_id: '13353'
abstract:
- lang: eng
text: We show that the optical properties of indigo carmine can be modulated by
encapsulation within a coordination cage. Depending on the host/guest molar ratio,
the cage can predominantly encapsulate either one or two dye molecules. The 1 : 1
complex is fluorescent, unique for an indigo dye in an aqueous solution. We have
also found that binding two dye molecules stabilizes a previously unknown conformation
of the cage.
article_processing_charge: No
article_type: original
author:
- first_name: Oksana
full_name: Yanshyna, Oksana
last_name: Yanshyna
- first_name: Liat
full_name: Avram, Liat
last_name: Avram
- first_name: Linda J. W.
full_name: Shimon, Linda J. W.
last_name: Shimon
- first_name: Rafal
full_name: Klajn, Rafal
id: 8e84690e-1e48-11ed-a02b-a1e6fb8bb53b
last_name: Klajn
citation:
ama: Yanshyna O, Avram L, Shimon LJW, Klajn R. Coexistence of 1:1 and 2:1 inclusion
complexes of indigo carmine. Chemical Communications. 2022;58(21):3461-3464.
doi:10.1039/d1cc07081a
apa: Yanshyna, O., Avram, L., Shimon, L. J. W., & Klajn, R. (2022). Coexistence
of 1:1 and 2:1 inclusion complexes of indigo carmine. Chemical Communications.
Royal Society of Chemistry. https://doi.org/10.1039/d1cc07081a
chicago: Yanshyna, Oksana, Liat Avram, Linda J. W. Shimon, and Rafal Klajn. “Coexistence
of 1:1 and 2:1 Inclusion Complexes of Indigo Carmine.” Chemical Communications.
Royal Society of Chemistry, 2022. https://doi.org/10.1039/d1cc07081a.
ieee: O. Yanshyna, L. Avram, L. J. W. Shimon, and R. Klajn, “Coexistence of 1:1
and 2:1 inclusion complexes of indigo carmine,” Chemical Communications,
vol. 58, no. 21. Royal Society of Chemistry, pp. 3461–3464, 2022.
ista: Yanshyna O, Avram L, Shimon LJW, Klajn R. 2022. Coexistence of 1:1 and 2:1
inclusion complexes of indigo carmine. Chemical Communications. 58(21), 3461–3464.
mla: Yanshyna, Oksana, et al. “Coexistence of 1:1 and 2:1 Inclusion Complexes of
Indigo Carmine.” Chemical Communications, vol. 58, no. 21, Royal Society
of Chemistry, 2022, pp. 3461–64, doi:10.1039/d1cc07081a.
short: O. Yanshyna, L. Avram, L.J.W. Shimon, R. Klajn, Chemical Communications 58
(2022) 3461–3464.
date_created: 2023-08-01T09:32:55Z
date_published: 2022-01-22T00:00:00Z
date_updated: 2023-08-02T09:46:51Z
day: '22'
doi: 10.1039/d1cc07081a
extern: '1'
external_id:
pmid:
- '35064258'
intvolume: ' 58'
issue: '21'
keyword:
- Materials Chemistry
- Metals and Alloys
- Surfaces
- Coatings and Films
- General Chemistry
- Ceramics and Composites
- Electronic
- Optical and Magnetic Materials
- Catalysis
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1039/D1CC07081A
month: '01'
oa: 1
oa_version: Published Version
page: 3461-3464
pmid: 1
publication: Chemical Communications
publication_identifier:
eissn:
- 1364-548X
issn:
- 1359-7345
publication_status: published
publisher: Royal Society of Chemistry
quality_controlled: '1'
scopus_import: '1'
status: public
title: Coexistence of 1:1 and 2:1 inclusion complexes of indigo carmine
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 58
year: '2022'
...
---
_id: '13355'
abstract:
- lang: eng
text: 'Supramolecular self-assembly in biological systems holds promise to convert
and amplify disease-specific signals to physical or mechanical signals that can
direct cell fate. However, it remains challenging to design physiologically stable
self-assembling systems that demonstrate tunable and predictable behavior. Here,
the use of zwitterionic tetrapeptide modalities to direct nanoparticle assembly
under physiological conditions is reported. The self-assembly of gold nanoparticles
can be activated by enzymatic unveiling of surface-bound zwitterionic tetrapeptides
through matrix metalloprotease-9 (MMP-9), which is overexpressed by cancer cells.
This robust nanoparticle assembly is achieved by multivalent, self-complementary
interactions of the zwitterionic tetrapeptides. In cancer cells that overexpress
MMP-9, the nanoparticle assembly process occurs near the cell membrane and causes
size-induced selection of cellular uptake mechanism, resulting in diminished cell
growth. The enzyme responsiveness, and therefore, indirectly, the uptake route
of the system can be programmed by customizing the peptide sequence: a simple
inversion of the two amino acids at the cleavage site completely inactivates the
enzyme responsiveness, self-assembly, and consequently changes the endocytic pathway.
This robust self-complementary, zwitterionic peptide design demonstrates the use
of enzyme-activated electrostatic side-chain patterns as powerful and customizable
peptide modalities to program nanoparticle self-assembly and alter cellular response
in biological context.'
article_number: '2104962'
article_processing_charge: No
article_type: original
author:
- first_name: Richard H.
full_name: Huang, Richard H.
last_name: Huang
- first_name: Nazia
full_name: Nayeem, Nazia
last_name: Nayeem
- first_name: Ye
full_name: He, Ye
last_name: He
- first_name: Jorge
full_name: Morales, Jorge
last_name: Morales
- first_name: Duncan
full_name: Graham, Duncan
last_name: Graham
- first_name: Rafal
full_name: Klajn, Rafal
id: 8e84690e-1e48-11ed-a02b-a1e6fb8bb53b
last_name: Klajn
- first_name: Maria
full_name: Contel, Maria
last_name: Contel
- first_name: Stephen
full_name: O'Brien, Stephen
last_name: O'Brien
- first_name: Rein V.
full_name: Ulijn, Rein V.
last_name: Ulijn
citation:
ama: Huang RH, Nayeem N, He Y, et al. Self‐complementary zwitterionic peptides direct
nanoparticle assembly and enable enzymatic selection of endocytic pathways. Advanced
Materials. 2022;34(1). doi:10.1002/adma.202104962
apa: Huang, R. H., Nayeem, N., He, Y., Morales, J., Graham, D., Klajn, R., … Ulijn,
R. V. (2022). Self‐complementary zwitterionic peptides direct nanoparticle assembly
and enable enzymatic selection of endocytic pathways. Advanced Materials.
Wiley. https://doi.org/10.1002/adma.202104962
chicago: Huang, Richard H., Nazia Nayeem, Ye He, Jorge Morales, Duncan Graham, Rafal
Klajn, Maria Contel, Stephen O’Brien, and Rein V. Ulijn. “Self‐complementary Zwitterionic
Peptides Direct Nanoparticle Assembly and Enable Enzymatic Selection of Endocytic
Pathways.” Advanced Materials. Wiley, 2022. https://doi.org/10.1002/adma.202104962.
ieee: R. H. Huang et al., “Self‐complementary zwitterionic peptides direct
nanoparticle assembly and enable enzymatic selection of endocytic pathways,” Advanced
Materials, vol. 34, no. 1. Wiley, 2022.
ista: Huang RH, Nayeem N, He Y, Morales J, Graham D, Klajn R, Contel M, O’Brien
S, Ulijn RV. 2022. Self‐complementary zwitterionic peptides direct nanoparticle
assembly and enable enzymatic selection of endocytic pathways. Advanced Materials.
34(1), 2104962.
mla: Huang, Richard H., et al. “Self‐complementary Zwitterionic Peptides Direct
Nanoparticle Assembly and Enable Enzymatic Selection of Endocytic Pathways.” Advanced
Materials, vol. 34, no. 1, 2104962, Wiley, 2022, doi:10.1002/adma.202104962.
short: R.H. Huang, N. Nayeem, Y. He, J. Morales, D. Graham, R. Klajn, M. Contel,
S. O’Brien, R.V. Ulijn, Advanced Materials 34 (2022).
date_created: 2023-08-01T09:33:26Z
date_published: 2022-01-06T00:00:00Z
date_updated: 2023-08-07T09:58:17Z
day: '06'
doi: 10.1002/adma.202104962
extern: '1'
external_id:
pmid:
- '34668253'
intvolume: ' 34'
issue: '1'
keyword:
- Mechanical Engineering
- Mechanics of Materials
- General Materials Science
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1002/adma.202104962
month: '01'
oa: 1
oa_version: Published Version
pmid: 1
publication: Advanced Materials
publication_identifier:
eissn:
- 1521-4095
issn:
- 0935-9648
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Self‐complementary zwitterionic peptides direct nanoparticle assembly and enable
enzymatic selection of endocytic pathways
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2022'
...
---
_id: '13445'
abstract:
- lang: eng
text: Rotation is typically assumed to induce strictly symmetric rotational splitting
into the rotational multiplets of pure p- and g-modes. However, for evolved stars
exhibiting mixed modes, avoided crossings between different multiplet components
are known to yield asymmetric rotational splitting, in particular for near-degenerate
mixed-mode pairs, where notional pure p-modes are fortuitously in resonance with
pure g-modes. These near-degeneracy effects have been described in subgiants,
but their consequences for the characterization of internal rotation in red giants
have not previously been investigated in detail, in part owing to theoretical
intractability. We employ new developments in the analytic theory of mixed-mode
coupling to study these near-resonance phenomena. In the vicinity of the most
p-dominated mixed modes, the near-degenerate intrinsic asymmetry from pure rotational
splitting increases dramatically over the course of stellar evolution, and it
depends strongly on the mode-mixing fraction ζ. We also find that a linear treatment
of rotation remains viable for describing the underlying p- and g-modes, even
when it does not for the resulting mixed modes undergoing these avoided crossings.
We explore observational consequences for potential measurements of asymmetric
mixed-mode splitting, which has been proposed as a magnetic-field diagnostic.
Finally, we propose improved measurement techniques for rotational characterization,
exploiting the linearity of rotational effects on the underlying p/g-modes, while
still accounting for these mixed-mode coupling effects.
article_number: '18'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: J. M. Joel
full_name: Ong, J. M. Joel
last_name: Ong
- first_name: Lisa Annabelle
full_name: Bugnet, Lisa Annabelle
id: d9edb345-f866-11ec-9b37-d119b5234501
last_name: Bugnet
orcid: 0000-0003-0142-4000
- first_name: Sarbani
full_name: Basu, Sarbani
last_name: Basu
citation:
ama: Ong JMJ, Bugnet LA, Basu S. Mode mixing and rotational splittings. I. Near-degeneracy
effects revisited. The Astrophysical Journal. 2022;940(1). doi:10.3847/1538-4357/ac97e7
apa: Ong, J. M. J., Bugnet, L. A., & Basu, S. (2022). Mode mixing and rotational
splittings. I. Near-degeneracy effects revisited. The Astrophysical Journal.
American Astronomical Society. https://doi.org/10.3847/1538-4357/ac97e7
chicago: Ong, J. M. Joel, Lisa Annabelle Bugnet, and Sarbani Basu. “Mode Mixing
and Rotational Splittings. I. Near-Degeneracy Effects Revisited.” The Astrophysical
Journal. American Astronomical Society, 2022. https://doi.org/10.3847/1538-4357/ac97e7.
ieee: J. M. J. Ong, L. A. Bugnet, and S. Basu, “Mode mixing and rotational splittings.
I. Near-degeneracy effects revisited,” The Astrophysical Journal, vol.
940, no. 1. American Astronomical Society, 2022.
ista: Ong JMJ, Bugnet LA, Basu S. 2022. Mode mixing and rotational splittings. I.
Near-degeneracy effects revisited. The Astrophysical Journal. 940(1), 18.
mla: Ong, J. M. Joel, et al. “Mode Mixing and Rotational Splittings. I. Near-Degeneracy
Effects Revisited.” The Astrophysical Journal, vol. 940, no. 1, 18, American
Astronomical Society, 2022, doi:10.3847/1538-4357/ac97e7.
short: J.M.J. Ong, L.A. Bugnet, S. Basu, The Astrophysical Journal 940 (2022).
date_created: 2023-08-01T14:20:41Z
date_published: 2022-11-16T00:00:00Z
date_updated: 2023-09-06T07:27:45Z
day: '16'
doi: 10.3847/1538-4357/ac97e7
extern: '1'
external_id:
arxiv:
- '2210.01928'
intvolume: ' 940'
issue: '1'
keyword:
- Space and Planetary Science
- Astronomy and Astrophysics
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2210.01928
month: '11'
oa: 1
oa_version: Published Version
publication: The Astrophysical Journal
publication_identifier:
eissn:
- 1538-4357
issn:
- 0004-637X
publication_status: published
publisher: American Astronomical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Mode mixing and rotational splittings. I. Near-degeneracy effects revisited
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 940
year: '2022'
...
---
_id: '13451'
abstract:
- lang: eng
text: 'We characterize massive stars (M > 8 M⊙) in the nearby (D ∼ 0.8 Mpc) extremely
metal-poor (Z ∼ 5% Z⊙) galaxy Leo A using Hubble Space Telescope ultraviolet (UV),
optical, and near-infrared (NIR) imaging along with Keck/Low-Resolution Imaging
Spectrograph and MMT/Binospec optical spectroscopy for 18 main-sequence OB stars.
We find that: (a) 12 of our 18 stars show emission lines, despite not being associated
with an H ii region, suggestive of stellar activity (e.g., mass loss, accretion,
binary star interaction), which is consistent with previous predictions of enhanced
activity at low metallicity; (b) six are Be stars, which are the first to be spectroscopically
studied at such low metallicity—these Be stars have unusual panchromatic SEDs;
(c) for stars well fit by the TLUSTY nonlocal thermodynamic equilibrium models,
the photometric and spectroscopic values of $\mathrm{log}({T}_{\mathrm{eff}})$
and $\mathrm{log}(g)$ agree to within ∼0.01 dex and ∼0.18 dex, respectively, indicating
that near-UV/optical/NIR imaging can be used to reliably characterize massive
(M ∼ 8–30 M⊙) main-sequence star properties relative to optical spectroscopy;
(d) the properties of the most-massive stars in H II regions are consistent with
constraints from previous nebular emission line studies; and (e) 13 stars with
M > 8M⊙ are >40 pc from a known star cluster or H II region. Our sample comprises
∼50% of all known massive stars at Z ≲ 10% Z⊙with derived stellar parameters,
high-quality optical spectra, and panchromatic photometry.'
article_number: '206'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Maude
full_name: Gull, Maude
last_name: Gull
- first_name: Daniel R.
full_name: Weisz, Daniel R.
last_name: Weisz
- first_name: Peter
full_name: Senchyna, Peter
last_name: Senchyna
- first_name: Nathan R.
full_name: Sandford, Nathan R.
last_name: Sandford
- first_name: Yumi
full_name: Choi, Yumi
last_name: Choi
- first_name: Anna F.
full_name: McLeod, Anna F.
last_name: McLeod
- first_name: Kareem
full_name: El-Badry, Kareem
last_name: El-Badry
- first_name: Ylva Louise Linsdotter
full_name: Götberg, Ylva Louise Linsdotter
id: d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d
last_name: Götberg
orcid: 0000-0002-6960-6911
- first_name: Karoline M.
full_name: Gilbert, Karoline M.
last_name: Gilbert
- first_name: Martha
full_name: Boyer, Martha
last_name: Boyer
- first_name: Julianne J.
full_name: Dalcanton, Julianne J.
last_name: Dalcanton
- first_name: Puragra
full_name: GuhaThakurta, Puragra
last_name: GuhaThakurta
- first_name: Steven
full_name: Goldman, Steven
last_name: Goldman
- first_name: Paola
full_name: Marigo, Paola
last_name: Marigo
- first_name: Kristen B. W.
full_name: McQuinn, Kristen B. W.
last_name: McQuinn
- first_name: Giada
full_name: Pastorelli, Giada
last_name: Pastorelli
- first_name: Daniel P.
full_name: Stark, Daniel P.
last_name: Stark
- first_name: Evan
full_name: Skillman, Evan
last_name: Skillman
- first_name: Yuan-sen
full_name: Ting, Yuan-sen
last_name: Ting
- first_name: Benjamin F.
full_name: Williams, Benjamin F.
last_name: Williams
citation:
ama: Gull M, Weisz DR, Senchyna P, et al. A panchromatic study of massive stars
in the extremely metal-poor local group dwarf galaxy Leo A. The Astrophysical
Journal. 2022;941(2). doi:10.3847/1538-4357/aca295
apa: Gull, M., Weisz, D. R., Senchyna, P., Sandford, N. R., Choi, Y., McLeod, A.
F., … Williams, B. F. (2022). A panchromatic study of massive stars in the extremely
metal-poor local group dwarf galaxy Leo A. The Astrophysical Journal. American
Astronomical Society. https://doi.org/10.3847/1538-4357/aca295
chicago: Gull, Maude, Daniel R. Weisz, Peter Senchyna, Nathan R. Sandford, Yumi
Choi, Anna F. McLeod, Kareem El-Badry, et al. “A Panchromatic Study of Massive
Stars in the Extremely Metal-Poor Local Group Dwarf Galaxy Leo A.” The Astrophysical
Journal. American Astronomical Society, 2022. https://doi.org/10.3847/1538-4357/aca295.
ieee: M. Gull et al., “A panchromatic study of massive stars in the extremely
metal-poor local group dwarf galaxy Leo A,” The Astrophysical Journal,
vol. 941, no. 2. American Astronomical Society, 2022.
ista: Gull M, Weisz DR, Senchyna P, Sandford NR, Choi Y, McLeod AF, El-Badry K,
Götberg YLL, Gilbert KM, Boyer M, Dalcanton JJ, GuhaThakurta P, Goldman S, Marigo
P, McQuinn KBW, Pastorelli G, Stark DP, Skillman E, Ting Y, Williams BF. 2022.
A panchromatic study of massive stars in the extremely metal-poor local group
dwarf galaxy Leo A. The Astrophysical Journal. 941(2), 206.
mla: Gull, Maude, et al. “A Panchromatic Study of Massive Stars in the Extremely
Metal-Poor Local Group Dwarf Galaxy Leo A.” The Astrophysical Journal,
vol. 941, no. 2, 206, American Astronomical Society, 2022, doi:10.3847/1538-4357/aca295.
short: M. Gull, D.R. Weisz, P. Senchyna, N.R. Sandford, Y. Choi, A.F. McLeod, K.
El-Badry, Y.L.L. Götberg, K.M. Gilbert, M. Boyer, J.J. Dalcanton, P. GuhaThakurta,
S. Goldman, P. Marigo, K.B.W. McQuinn, G. Pastorelli, D.P. Stark, E. Skillman,
Y. Ting, B.F. Williams, The Astrophysical Journal 941 (2022).
date_created: 2023-08-03T10:10:25Z
date_published: 2022-12-27T00:00:00Z
date_updated: 2023-08-21T12:04:58Z
day: '27'
doi: 10.3847/1538-4357/aca295
extern: '1'
external_id:
arxiv:
- '2211.14349'
intvolume: ' 941'
issue: '2'
keyword:
- Space and Planetary Science
- Astronomy and Astrophysics
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.3847/1538-4357/aca295
month: '12'
oa: 1
oa_version: Published Version
publication: The Astrophysical Journal
publication_identifier:
eissn:
- 1538-4357
issn:
- 0004-637X
publication_status: published
publisher: American Astronomical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: A panchromatic study of massive stars in the extremely metal-poor local group
dwarf galaxy Leo A
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 941
year: '2022'
...
---
_id: '13452'
abstract:
- lang: eng
text: Magnetic fields can drastically change predictions of evolutionary models
of massive stars via mass-loss quenching, magnetic braking, and efficient angular
momentum transport, which we aim to quantify in this work. We use the MESA software
instrument to compute an extensive main-sequence grid of stellar structure and
evolution models, as well as isochrones, accounting for the effects attributed
to a surface fossil magnetic field. The grid is densely populated in initial mass
(3–60 M⊙), surface equatorial magnetic field strength (0–50 kG), and metallicity
(representative of the Solar neighbourhood and the Magellanic Clouds). We use
two magnetic braking and two chemical mixing schemes and compare the model predictions
for slowly rotating, nitrogen-enriched (‘Group 2’) stars with observations in
the Large Magellanic Cloud. We quantify a range of initial field strengths that
allow for producing Group 2 stars and find that typical values (up to a few kG)
lead to solutions. Between the subgrids, we find notable departures in surface
abundances and evolutionary paths. In our magnetic models, chemical mixing is
always less efficient compared to non-magnetic models due to the rapid spin-down.
We identify that quasi-chemically homogeneous main sequence evolution by efficient
mixing could be prevented by fossil magnetic fields. We recommend comparing this
grid of evolutionary models with spectropolarimetric and spectroscopic observations
with the goals of (i) revisiting the derived stellar parameters of known magnetic
stars, and (ii) observationally constraining the uncertain magnetic braking and
chemical mixing schemes.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Z
full_name: Keszthelyi, Z
last_name: Keszthelyi
- first_name: A
full_name: de Koter, A
last_name: de Koter
- first_name: Ylva Louise Linsdotter
full_name: Götberg, Ylva Louise Linsdotter
id: d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d
last_name: Götberg
orcid: 0000-0002-6960-6911
- first_name: G
full_name: Meynet, G
last_name: Meynet
- first_name: S A
full_name: Brands, S A
last_name: Brands
- first_name: V
full_name: Petit, V
last_name: Petit
- first_name: M
full_name: Carrington, M
last_name: Carrington
- first_name: A
full_name: David-Uraz, A
last_name: David-Uraz
- first_name: S T
full_name: Geen, S T
last_name: Geen
- first_name: C
full_name: Georgy, C
last_name: Georgy
- first_name: R
full_name: Hirschi, R
last_name: Hirschi
- first_name: J
full_name: Puls, J
last_name: Puls
- first_name: K J
full_name: Ramalatswa, K J
last_name: Ramalatswa
- first_name: M E
full_name: Shultz, M E
last_name: Shultz
- first_name: A
full_name: ud-Doula, A
last_name: ud-Doula
citation:
ama: 'Keszthelyi Z, de Koter A, Götberg YLL, et al. The effects of surface fossil
magnetic fields on massive star evolution: IV. Grids of models at Solar, LMC,
and SMC metallicities. Monthly Notices of the Royal Astronomical Society.
2022;517(2):2028-2055. doi:10.1093/mnras/stac2598'
apa: 'Keszthelyi, Z., de Koter, A., Götberg, Y. L. L., Meynet, G., Brands, S. A.,
Petit, V., … ud-Doula, A. (2022). The effects of surface fossil magnetic fields
on massive star evolution: IV. Grids of models at Solar, LMC, and SMC metallicities.
Monthly Notices of the Royal Astronomical Society. Oxford University Press.
https://doi.org/10.1093/mnras/stac2598'
chicago: 'Keszthelyi, Z, A de Koter, Ylva Louise Linsdotter Götberg, G Meynet, S
A Brands, V Petit, M Carrington, et al. “The Effects of Surface Fossil Magnetic
Fields on Massive Star Evolution: IV. Grids of Models at Solar, LMC, and SMC Metallicities.”
Monthly Notices of the Royal Astronomical Society. Oxford University Press,
2022. https://doi.org/10.1093/mnras/stac2598.'
ieee: 'Z. Keszthelyi et al., “The effects of surface fossil magnetic fields
on massive star evolution: IV. Grids of models at Solar, LMC, and SMC metallicities,”
Monthly Notices of the Royal Astronomical Society, vol. 517, no. 2. Oxford
University Press, pp. 2028–2055, 2022.'
ista: 'Keszthelyi Z, de Koter A, Götberg YLL, Meynet G, Brands SA, Petit V, Carrington
M, David-Uraz A, Geen ST, Georgy C, Hirschi R, Puls J, Ramalatswa KJ, Shultz ME,
ud-Doula A. 2022. The effects of surface fossil magnetic fields on massive star
evolution: IV. Grids of models at Solar, LMC, and SMC metallicities. Monthly Notices
of the Royal Astronomical Society. 517(2), 2028–2055.'
mla: 'Keszthelyi, Z., et al. “The Effects of Surface Fossil Magnetic Fields on Massive
Star Evolution: IV. Grids of Models at Solar, LMC, and SMC Metallicities.” Monthly
Notices of the Royal Astronomical Society, vol. 517, no. 2, Oxford University
Press, 2022, pp. 2028–55, doi:10.1093/mnras/stac2598.'
short: Z. Keszthelyi, A. de Koter, Y.L.L. Götberg, G. Meynet, S.A. Brands, V. Petit,
M. Carrington, A. David-Uraz, S.T. Geen, C. Georgy, R. Hirschi, J. Puls, K.J.
Ramalatswa, M.E. Shultz, A. ud-Doula, Monthly Notices of the Royal Astronomical
Society 517 (2022) 2028–2055.
date_created: 2023-08-03T10:10:37Z
date_published: 2022-12-01T00:00:00Z
date_updated: 2023-08-21T12:02:17Z
day: '01'
doi: 10.1093/mnras/stac2598
extern: '1'
external_id:
arxiv:
- '2209.06350'
intvolume: ' 517'
issue: '2'
keyword:
- Space and Planetary Science
- Astronomy and Astrophysics
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2209.06350
month: '12'
oa: 1
oa_version: Preprint
page: 2028-2055
publication: Monthly Notices of the Royal Astronomical Society
publication_identifier:
eissn:
- 1365-2966
issn:
- 0035-8711
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'The effects of surface fossil magnetic fields on massive star evolution: IV.
Grids of models at Solar, LMC, and SMC metallicities'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 517
year: '2022'
...
---
_id: '13992'
abstract:
- lang: eng
text: Understanding the chirality of molecular reaction pathways is essential for
a broad range of fundamental and applied sciences. However, the current ability
to probe chirality on the time scale of primary processes underlying chemical
reactions remains very limited. Here, we demonstrate time-resolved photoelectron
circular dichroism (TRPECD) with ultrashort circularly polarized vacuum-ultraviolet
(VUV) pulses from a tabletop source. We demonstrate the capabilities of VUV-TRPECD
by resolving the chirality changes in time during the photodissociation of atomic
iodine from two chiral molecules. We identify several general key features of
TRPECD, which include the ability to probe dynamical chirality along the complete
photochemical reaction path, the sensitivity to the local chirality of the evolving
scattering potential, and the influence of electron scattering off dissociating
photofragments. Our results are interpreted by comparison with high-level ab-initio
calculations of transient PECDs from molecular photoionization calculations. Our
experimental and theoretical techniques define a general approach to femtochirality.
article_number: abq2811
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Vít
full_name: Svoboda, Vít
last_name: Svoboda
- first_name: Niraghatam Bhargava
full_name: Ram, Niraghatam Bhargava
last_name: Ram
- first_name: Denitsa Rangelova
full_name: Baykusheva, Denitsa Rangelova
id: 71b4d059-2a03-11ee-914d-dfa3beed6530
last_name: Baykusheva
- first_name: Daniel
full_name: Zindel, Daniel
last_name: Zindel
- first_name: Max D. J.
full_name: Waters, Max D. J.
last_name: Waters
- first_name: Benjamin
full_name: Spenger, Benjamin
last_name: Spenger
- first_name: Manuel
full_name: Ochsner, Manuel
last_name: Ochsner
- first_name: Holger
full_name: Herburger, Holger
last_name: Herburger
- first_name: Jürgen
full_name: Stohner, Jürgen
last_name: Stohner
- first_name: Hans Jakob
full_name: Wörner, Hans Jakob
last_name: Wörner
citation:
ama: Svoboda V, Ram NB, Baykusheva DR, et al. Femtosecond photoelectron circular
dichroism of chemical reactions. Science Advances. 2022;8(28). doi:10.1126/sciadv.abq2811
apa: Svoboda, V., Ram, N. B., Baykusheva, D. R., Zindel, D., Waters, M. D. J., Spenger,
B., … Wörner, H. J. (2022). Femtosecond photoelectron circular dichroism of chemical
reactions. Science Advances. American Association for the Advancement of
Science. https://doi.org/10.1126/sciadv.abq2811
chicago: Svoboda, Vít, Niraghatam Bhargava Ram, Denitsa Rangelova Baykusheva, Daniel
Zindel, Max D. J. Waters, Benjamin Spenger, Manuel Ochsner, Holger Herburger,
Jürgen Stohner, and Hans Jakob Wörner. “Femtosecond Photoelectron Circular Dichroism
of Chemical Reactions.” Science Advances. American Association for the
Advancement of Science, 2022. https://doi.org/10.1126/sciadv.abq2811.
ieee: V. Svoboda et al., “Femtosecond photoelectron circular dichroism of
chemical reactions,” Science Advances, vol. 8, no. 28. American Association
for the Advancement of Science, 2022.
ista: Svoboda V, Ram NB, Baykusheva DR, Zindel D, Waters MDJ, Spenger B, Ochsner
M, Herburger H, Stohner J, Wörner HJ. 2022. Femtosecond photoelectron circular
dichroism of chemical reactions. Science Advances. 8(28), abq2811.
mla: Svoboda, Vít, et al. “Femtosecond Photoelectron Circular Dichroism of Chemical
Reactions.” Science Advances, vol. 8, no. 28, abq2811, American Association
for the Advancement of Science, 2022, doi:10.1126/sciadv.abq2811.
short: V. Svoboda, N.B. Ram, D.R. Baykusheva, D. Zindel, M.D.J. Waters, B. Spenger,
M. Ochsner, H. Herburger, J. Stohner, H.J. Wörner, Science Advances 8 (2022).
date_created: 2023-08-09T13:08:04Z
date_published: 2022-07-15T00:00:00Z
date_updated: 2023-08-22T07:24:01Z
day: '15'
doi: 10.1126/sciadv.abq2811
extern: '1'
external_id:
arxiv:
- '2206.04099'
pmid:
- '35857523'
intvolume: ' 8'
issue: '28'
keyword:
- Multidisciplinary
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1126/sciadv.abq2811
month: '07'
oa: 1
oa_version: Published Version
pmid: 1
publication: Science Advances
publication_identifier:
eissn:
- 2375-2548
publication_status: published
publisher: American Association for the Advancement of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Femtosecond photoelectron circular dichroism of chemical reactions
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2022'
...
---
_id: '13993'
abstract:
- lang: eng
text: Photoionization is a process taking place on attosecond time scales. How its
properties evolve from isolated particles to the condensed phase is an open question
of both fundamental and practical relevance. Here, we review recent work that
has advanced the study of photoionization dynamics from atoms to molecules, clusters
and the liquid phase. The first measurements of molecular photoionization delays
have revealed the attosecond dynamics of electron emission from a molecular shape
resonance and their sensitivity to the molecular potential. Using electron-ion
coincidence spectroscopy these measurements have been extended from isolated molecules
to clusters. A continuous increase of the delays with the water-cluster size has
been observed up to a size of 4-5 molecules, followed by a saturation towards
larger clusters. Comparison with calculations has revealed a correlation of the
time delay with the spatial extension of the created electron hole. Using cylindrical
liquid-microjet techniques, these measurements have also been extended to liquid
water, revealing a delay relative to isolated water molecules that was very similar
to the largest water clusters studied. Detailed modeling based on Monte-Carlo
simulations confirmed that these delays are dominated by the contributions of
the first two solvation shells, which agrees with the results of the cluster measurements.
These combined results open the perspective of experimentally characterizing the
delocalization of electronic wave functions in complex systems and studying their
evolution on attosecond time scales.
article_processing_charge: No
article_type: original
author:
- first_name: Xiaochun
full_name: Gong, Xiaochun
last_name: Gong
- first_name: Inga
full_name: Jordan, Inga
last_name: Jordan
- first_name: Martin
full_name: Huppert, Martin
last_name: Huppert
- first_name: Saijoscha
full_name: Heck, Saijoscha
last_name: Heck
- first_name: Denitsa Rangelova
full_name: Baykusheva, Denitsa Rangelova
id: 71b4d059-2a03-11ee-914d-dfa3beed6530
last_name: Baykusheva
- first_name: Denis
full_name: Jelovina, Denis
last_name: Jelovina
- first_name: Axel
full_name: Schild, Axel
last_name: Schild
- first_name: Hans Jakob
full_name: Wörner, Hans Jakob
last_name: Wörner
citation:
ama: 'Gong X, Jordan I, Huppert M, et al. Attosecond photoionization dynamics: from
molecules over clusters to the liquid phase. Chimia. 2022;76(6):520-528.
doi:10.2533/chimia.2022.520'
apa: 'Gong, X., Jordan, I., Huppert, M., Heck, S., Baykusheva, D. R., Jelovina,
D., … Wörner, H. J. (2022). Attosecond photoionization dynamics: from molecules
over clusters to the liquid phase. Chimia. Swiss Chemical Society. https://doi.org/10.2533/chimia.2022.520'
chicago: 'Gong, Xiaochun, Inga Jordan, Martin Huppert, Saijoscha Heck, Denitsa Rangelova
Baykusheva, Denis Jelovina, Axel Schild, and Hans Jakob Wörner. “Attosecond Photoionization
Dynamics: From Molecules over Clusters to the Liquid Phase.” Chimia. Swiss
Chemical Society, 2022. https://doi.org/10.2533/chimia.2022.520.'
ieee: 'X. Gong et al., “Attosecond photoionization dynamics: from molecules
over clusters to the liquid phase,” Chimia, vol. 76, no. 6. Swiss Chemical
Society, pp. 520–528, 2022.'
ista: 'Gong X, Jordan I, Huppert M, Heck S, Baykusheva DR, Jelovina D, Schild A,
Wörner HJ. 2022. Attosecond photoionization dynamics: from molecules over clusters
to the liquid phase. Chimia. 76(6), 520–528.'
mla: 'Gong, Xiaochun, et al. “Attosecond Photoionization Dynamics: From Molecules
over Clusters to the Liquid Phase.” Chimia, vol. 76, no. 6, Swiss Chemical
Society, 2022, pp. 520–28, doi:10.2533/chimia.2022.520.'
short: X. Gong, I. Jordan, M. Huppert, S. Heck, D.R. Baykusheva, D. Jelovina, A.
Schild, H.J. Wörner, Chimia 76 (2022) 520–528.
date_created: 2023-08-09T13:08:15Z
date_published: 2022-06-29T00:00:00Z
date_updated: 2023-08-22T07:26:39Z
day: '29'
doi: 10.2533/chimia.2022.520
extern: '1'
intvolume: ' 76'
issue: '6'
keyword:
- General Medicine
- General Chemistry
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.2533/chimia.2022.520
month: '06'
oa: 1
oa_version: Published Version
page: 520-528
publication: Chimia
publication_identifier:
eissn:
- 2673-2424
issn:
- 0009-4293
publication_status: published
publisher: Swiss Chemical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Attosecond photoionization dynamics: from molecules over clusters to the liquid
phase'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 76
year: '2022'
...
---
_id: '13994'
abstract:
- lang: eng
text: "Ultrafast lasers are an increasingly important tool to control and stabilize
emergent phases in quantum materials. Among a variety of possible excitation protocols,
a particularly intriguing route is the direct light engineering of microscopic
electronic parameters, such as the electron hopping and the local Coulomb repulsion
(Hubbard \r\nU). In this work, we use time-resolved x-ray absorption spectroscopy
to demonstrate the light-induced renormalization of the Hubbard U in a cuprate
superconductor, La1.905Ba0.095CuO4. We show that intense femtosecond laser pulses
induce a substantial redshift of the upper Hubbard band while leaving the Zhang-Rice
singlet energy unaffected. By comparing the experimental data to time-dependent
spectra of single- and three-band Hubbard models, we assign this effect to an
approximately 140-meV reduction of the on-site Coulomb repulsion on the copper
sites. Our demonstration of a dynamical Hubbard U renormalization in a copper
oxide paves the way to a novel strategy for the manipulation of superconductivity
and magnetism as well as to the realization of other long-range-ordered phases
in light-driven quantum materials."
article_number: '011013'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Denitsa Rangelova
full_name: Baykusheva, Denitsa Rangelova
id: 71b4d059-2a03-11ee-914d-dfa3beed6530
last_name: Baykusheva
- first_name: Hoyoung
full_name: Jang, Hoyoung
last_name: Jang
- first_name: Ali A.
full_name: Husain, Ali A.
last_name: Husain
- first_name: Sangjun
full_name: Lee, Sangjun
last_name: Lee
- first_name: Sophia F. R.
full_name: TenHuisen, Sophia F. R.
last_name: TenHuisen
- first_name: Preston
full_name: Zhou, Preston
last_name: Zhou
- first_name: Sunwook
full_name: Park, Sunwook
last_name: Park
- first_name: Hoon
full_name: Kim, Hoon
last_name: Kim
- first_name: Jin-Kwang
full_name: Kim, Jin-Kwang
last_name: Kim
- first_name: Hyeong-Do
full_name: Kim, Hyeong-Do
last_name: Kim
- first_name: Minseok
full_name: Kim, Minseok
last_name: Kim
- first_name: Sang-Youn
full_name: Park, Sang-Youn
last_name: Park
- first_name: Peter
full_name: Abbamonte, Peter
last_name: Abbamonte
- first_name: B. J.
full_name: Kim, B. J.
last_name: Kim
- first_name: G. D.
full_name: Gu, G. D.
last_name: Gu
- first_name: Yao
full_name: Wang, Yao
last_name: Wang
- first_name: Matteo
full_name: Mitrano, Matteo
last_name: Mitrano
citation:
ama: Baykusheva DR, Jang H, Husain AA, et al. Ultrafast renormalization of the on-site
Coulomb repulsion in a cuprate superconductor. Physical Review X. 2022;12(1).
doi:10.1103/physrevx.12.011013
apa: Baykusheva, D. R., Jang, H., Husain, A. A., Lee, S., TenHuisen, S. F. R., Zhou,
P., … Mitrano, M. (2022). Ultrafast renormalization of the on-site Coulomb repulsion
in a cuprate superconductor. Physical Review X. American Physical Society.
https://doi.org/10.1103/physrevx.12.011013
chicago: Baykusheva, Denitsa Rangelova, Hoyoung Jang, Ali A. Husain, Sangjun Lee,
Sophia F. R. TenHuisen, Preston Zhou, Sunwook Park, et al. “Ultrafast Renormalization
of the On-Site Coulomb Repulsion in a Cuprate Superconductor.” Physical Review
X. American Physical Society, 2022. https://doi.org/10.1103/physrevx.12.011013.
ieee: D. R. Baykusheva et al., “Ultrafast renormalization of the on-site
Coulomb repulsion in a cuprate superconductor,” Physical Review X, vol.
12, no. 1. American Physical Society, 2022.
ista: Baykusheva DR, Jang H, Husain AA, Lee S, TenHuisen SFR, Zhou P, Park S, Kim
H, Kim J-K, Kim H-D, Kim M, Park S-Y, Abbamonte P, Kim BJ, Gu GD, Wang Y, Mitrano
M. 2022. Ultrafast renormalization of the on-site Coulomb repulsion in a cuprate
superconductor. Physical Review X. 12(1), 011013.
mla: Baykusheva, Denitsa Rangelova, et al. “Ultrafast Renormalization of the On-Site
Coulomb Repulsion in a Cuprate Superconductor.” Physical Review X, vol.
12, no. 1, 011013, American Physical Society, 2022, doi:10.1103/physrevx.12.011013.
short: D.R. Baykusheva, H. Jang, A.A. Husain, S. Lee, S.F.R. TenHuisen, P. Zhou,
S. Park, H. Kim, J.-K. Kim, H.-D. Kim, M. Kim, S.-Y. Park, P. Abbamonte, B.J.
Kim, G.D. Gu, Y. Wang, M. Mitrano, Physical Review X 12 (2022).
date_created: 2023-08-09T13:08:26Z
date_published: 2022-01-20T00:00:00Z
date_updated: 2023-08-22T07:28:38Z
day: '20'
doi: 10.1103/physrevx.12.011013
extern: '1'
external_id:
arxiv:
- '2109.13229'
intvolume: ' 12'
issue: '1'
keyword:
- General Physics and Astronomy
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1103/PhysRevX.12.011013
month: '01'
oa: 1
oa_version: Published Version
publication: Physical Review X
publication_identifier:
eissn:
- 2160-3308
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Ultrafast renormalization of the on-site Coulomb repulsion in a cuprate superconductor
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 12
year: '2022'
...
---
_id: '14093'
abstract:
- lang: eng
text: ' We propose a stochastic conditional gradient method (CGM) for minimizing
convex finite-sum objectives formed as a sum of smooth and non-smooth terms. Existing
CGM variants for this template either suffer from slow convergence rates, or require
carefully increasing the batch size over the course of the algorithm’s execution,
which leads to computing full gradients. In contrast, the proposed method, equipped
with a stochastic average gradient (SAG) estimator, requires only one sample per
iteration. Nevertheless, it guarantees fast convergence rates on par with more
sophisticated variance reduction techniques. In applications we put special emphasis
on problems with a large number of separable constraints. Such problems are prevalent
among semidefinite programming (SDP) formulations arising in machine learning
and theoretical computer science. We provide numerical experiments on matrix completion,
unsupervised clustering, and sparsest-cut SDPs. '
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Gideon
full_name: Dresdner, Gideon
last_name: Dresdner
- first_name: Maria-Luiza
full_name: Vladarean, Maria-Luiza
last_name: Vladarean
- first_name: Gunnar
full_name: Rätsch, Gunnar
last_name: Rätsch
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Volkan
full_name: Cevher, Volkan
last_name: Cevher
- first_name: Alp
full_name: Yurtsever, Alp
last_name: Yurtsever
citation:
ama: 'Dresdner G, Vladarean M-L, Rätsch G, Locatello F, Cevher V, Yurtsever A. Faster
one-sample stochastic conditional gradient method for composite convex minimization.
In: Proceedings of the 25th International Conference on Artificial Intelligence
and Statistics. Vol 151. ML Research Press; 2022:8439-8457.'
apa: 'Dresdner, G., Vladarean, M.-L., Rätsch, G., Locatello, F., Cevher, V., &
Yurtsever, A. (2022). Faster one-sample stochastic conditional gradient method
for composite convex minimization. In Proceedings of the 25th International
Conference on Artificial Intelligence and Statistics (Vol. 151, pp. 8439–8457).
Virtual: ML Research Press.'
chicago: Dresdner, Gideon, Maria-Luiza Vladarean, Gunnar Rätsch, Francesco Locatello,
Volkan Cevher, and Alp Yurtsever. “ Faster One-Sample Stochastic Conditional Gradient
Method for Composite Convex Minimization.” In Proceedings of the 25th International
Conference on Artificial Intelligence and Statistics, 151:8439–57. ML Research
Press, 2022.
ieee: G. Dresdner, M.-L. Vladarean, G. Rätsch, F. Locatello, V. Cevher, and A. Yurtsever,
“ Faster one-sample stochastic conditional gradient method for composite convex
minimization,” in Proceedings of the 25th International Conference on Artificial
Intelligence and Statistics, Virtual, 2022, vol. 151, pp. 8439–8457.
ista: 'Dresdner G, Vladarean M-L, Rätsch G, Locatello F, Cevher V, Yurtsever A.
2022. Faster one-sample stochastic conditional gradient method for composite
convex minimization. Proceedings of the 25th International Conference on Artificial
Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and
Statistics, PMLR, vol. 151, 8439–8457.'
mla: Dresdner, Gideon, et al. “ Faster One-Sample Stochastic Conditional Gradient
Method for Composite Convex Minimization.” Proceedings of the 25th International
Conference on Artificial Intelligence and Statistics, vol. 151, ML Research
Press, 2022, pp. 8439–57.
short: G. Dresdner, M.-L. Vladarean, G. Rätsch, F. Locatello, V. Cevher, A. Yurtsever,
in:, Proceedings of the 25th International Conference on Artificial Intelligence
and Statistics, ML Research Press, 2022, pp. 8439–8457.
conference:
end_date: 2022-03-30
location: Virtual
name: 'AISTATS: Conference on Artificial Intelligence and Statistics'
start_date: 2022-03-28
date_created: 2023-08-21T09:27:43Z
date_published: 2022-04-01T00:00:00Z
date_updated: 2023-09-06T10:28:17Z
day: '01'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2202.13212'
intvolume: ' 151'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2202.13212
month: '04'
oa: 1
oa_version: Preprint
page: 8439-8457
publication: Proceedings of the 25th International Conference on Artificial Intelligence
and Statistics
publication_identifier:
issn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: ' Faster one-sample stochastic conditional gradient method for composite convex
minimization'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 151
year: '2022'
...
---
_id: '14098'
abstract:
- lang: eng
text: Magnetic fields can drastically change predictions of evolutionary models
of massive stars via mass-loss quenching, magnetic braking, and efficient angular
momentum transport, which we aim to quantify in this work. We use the MESA software
instrument to compute an extensive main-sequence grid of stellar structure and
evolution models, as well as isochrones, accounting for the effects attributed
to a surface fossil magnetic field. The grid is densely populated in initial mass
(3–60 M⊙), surface equatorial magnetic field strength (0–50 kG), and metallicity
(representative of the Solar neighbourhood and the Magellanic Clouds). We use
two magnetic braking and two chemical mixing schemes and compare the model predictions
for slowly rotating, nitrogen-enriched (‘Group 2’) stars with observations in
the Large Magellanic Cloud. We quantify a range of initial field strengths that
allow for producing Group 2 stars and find that typical values (up to a few kG)
lead to solutions. Between the subgrids, we find notable departures in surface
abundances and evolutionary paths. In our magnetic models, chemical mixing is
always less efficient compared to non-magnetic models due to the rapid spin-down.
We identify that quasi-chemically homogeneous main sequence evolution by efficient
mixing could be prevented by fossil magnetic fields. We recommend comparing this
grid of evolutionary models with spectropolarimetric and spectroscopic observations
with the goals of (i) revisiting the derived stellar parameters of known magnetic
stars, and (ii) observationally constraining the uncertain magnetic braking and
chemical mixing schemes.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Z.
full_name: Keszthelyi, Z.
last_name: Keszthelyi
- first_name: A. de
full_name: Koter, A. de
last_name: Koter
- first_name: Ylva Louise Linsdotter
full_name: Götberg, Ylva Louise Linsdotter
id: d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d
last_name: Götberg
orcid: 0000-0002-6960-6911
- first_name: G.
full_name: Meynet, G.
last_name: Meynet
- first_name: S. A.
full_name: Brands, S. A.
last_name: Brands
- first_name: V.
full_name: Petit, V.
last_name: Petit
- first_name: M.
full_name: Carrington, M.
last_name: Carrington
- first_name: A. David-Uraz
full_name: A. David-Uraz, A. David-Uraz
last_name: A. David-Uraz
- first_name: S. T.
full_name: Geen, S. T.
last_name: Geen
- first_name: C.
full_name: Georgy, C.
last_name: Georgy
- first_name: R.
full_name: Hirschi, R.
last_name: Hirschi
- first_name: J.
full_name: Puls, J.
last_name: Puls
- first_name: K. J.
full_name: Ramalatswa, K. J.
last_name: Ramalatswa
- first_name: M. E.
full_name: Shultz, M. E.
last_name: Shultz
- first_name: A. ud-Doula
full_name: A. ud-Doula, A. ud-Doula
last_name: A. ud-Doula
citation:
ama: 'Keszthelyi Z, Koter A de, Götberg YLL, et al. The effects of surface fossil
magnetic fields on massive star evolution: IV. Grids of models at solar, LMC,
and SMC metallicities. Monthly Notices of the Royal Astronomical Society.
2022;517(2):2028-2055. doi:10.1093/mnras/stac2598'
apa: 'Keszthelyi, Z., Koter, A. de, Götberg, Y. L. L., Meynet, G., Brands, S. A.,
Petit, V., … A. ud-Doula, A. ud-Doula. (2022). The effects of surface fossil magnetic
fields on massive star evolution: IV. Grids of models at solar, LMC, and SMC metallicities.
Monthly Notices of the Royal Astronomical Society. Oxford Academic. https://doi.org/10.1093/mnras/stac2598'
chicago: 'Keszthelyi, Z., A. de Koter, Ylva Louise Linsdotter Götberg, G. Meynet,
S. A. Brands, V. Petit, M. Carrington, et al. “The Effects of Surface Fossil Magnetic
Fields on Massive Star Evolution: IV. Grids of Models at Solar, LMC, and SMC Metallicities.”
Monthly Notices of the Royal Astronomical Society. Oxford Academic, 2022.
https://doi.org/10.1093/mnras/stac2598.'
ieee: 'Z. Keszthelyi et al., “The effects of surface fossil magnetic fields
on massive star evolution: IV. Grids of models at solar, LMC, and SMC metallicities,”
Monthly Notices of the Royal Astronomical Society, vol. 517, no. 2. Oxford
Academic, pp. 2028–2055, 2022.'
ista: 'Keszthelyi Z, Koter A de, Götberg YLL, Meynet G, Brands SA, Petit V, Carrington
M, A. David-Uraz AD-U, Geen ST, Georgy C, Hirschi R, Puls J, Ramalatswa KJ, Shultz
ME, A. ud-Doula A ud-Doula. 2022. The effects of surface fossil magnetic fields
on massive star evolution: IV. Grids of models at solar, LMC, and SMC metallicities.
Monthly Notices of the Royal Astronomical Society. 517(2), 2028–2055.'
mla: 'Keszthelyi, Z., et al. “The Effects of Surface Fossil Magnetic Fields on Massive
Star Evolution: IV. Grids of Models at Solar, LMC, and SMC Metallicities.” Monthly
Notices of the Royal Astronomical Society, vol. 517, no. 2, Oxford Academic,
2022, pp. 2028–55, doi:10.1093/mnras/stac2598.'
short: Z. Keszthelyi, A. de Koter, Y.L.L. Götberg, G. Meynet, S.A. Brands, V. Petit,
M. Carrington, A.D.-U. A. David-Uraz, S.T. Geen, C. Georgy, R. Hirschi, J. Puls,
K.J. Ramalatswa, M.E. Shultz, A. ud-Doula A. ud-Doula, Monthly Notices of the
Royal Astronomical Society 517 (2022) 2028–2055.
date_created: 2023-08-21T10:11:21Z
date_published: 2022-12-01T00:00:00Z
date_updated: 2023-08-22T13:18:34Z
day: '01'
doi: 10.1093/mnras/stac2598
extern: '1'
external_id:
arxiv:
- '2209.06350'
intvolume: ' 517'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1093/mnras/stac2598
month: '12'
oa: 1
oa_version: Published Version
page: 2028-2055
publication: Monthly Notices of the Royal Astronomical Society
publication_identifier:
eissn:
- 1365-2966
issn:
- 0035-8711
publication_status: published
publisher: Oxford Academic
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'The effects of surface fossil magnetic fields on massive star evolution: IV.
Grids of models at solar, LMC, and SMC metallicities'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 517
year: '2022'
...
---
_id: '14099'
abstract:
- lang: eng
text: Magnetism can greatly impact the evolution of stars. In some stars with OBA
spectral types there is direct evidence via the Zeeman effect for stable, large-scale
magnetospheres, which lead to the spin-down of the stellar surface and reduced
mass loss. So far, a comprehensive grid of stellar structure and evolution models
accounting for these effects was lacking. For this reason, we computed and studied
models with two magnetic braking and two chemical mixing schemes in three metallicity
environments with the MESA software instrument. We find notable differences between
the subgrids, which affects the model predictions and thus the detailed characterisation
of stars. We are able to quantify the impact of magnetic fields in terms of preventing
quasi-chemically homogeneous evolution and producing slowly-rotating, nitrogen-enriched
("Group 2") stars. Our model grid is fully open access and open source.
article_number: '2211.07060'
article_processing_charge: No
arxiv: 1
author:
- first_name: Z.
full_name: Keszthelyi, Z.
last_name: Keszthelyi
- first_name: A. de
full_name: Koter, A. de
last_name: Koter
- first_name: Ylva Louise Linsdotter
full_name: Götberg, Ylva Louise Linsdotter
id: d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d
last_name: Götberg
orcid: 0000-0002-6960-6911
- first_name: G.
full_name: Meynet, G.
last_name: Meynet
- first_name: S. A.
full_name: Brands, S. A.
last_name: Brands
- first_name: V.
full_name: Petit, V.
last_name: Petit
- first_name: M.
full_name: Carrington, M.
last_name: Carrington
- first_name: A. David-Uraz
full_name: A. David-Uraz, A. David-Uraz
last_name: A. David-Uraz
- first_name: S. T.
full_name: Geen, S. T.
last_name: Geen
- first_name: C.
full_name: Georgy, C.
last_name: Georgy
- first_name: R.
full_name: Hirschi, R.
last_name: Hirschi
- first_name: J.
full_name: Puls, J.
last_name: Puls
- first_name: K. J.
full_name: Ramalatswa, K. J.
last_name: Ramalatswa
- first_name: M. E.
full_name: Shultz, M. E.
last_name: Shultz
- first_name: A. ud-Doula
full_name: A. ud-Doula, A. ud-Doula
last_name: A. ud-Doula
citation:
ama: Keszthelyi Z, Koter A de, Götberg YLL, et al. Spin-down and reduced mass loss
in early-type stars with large-scale magnetic fields. arXiv. doi:10.48550/arXiv.2211.07060
apa: Keszthelyi, Z., Koter, A. de, Götberg, Y. L. L., Meynet, G., Brands, S. A.,
Petit, V., … A. ud-Doula, A. ud-Doula. (n.d.). Spin-down and reduced mass loss
in early-type stars with large-scale magnetic fields. arXiv. https://doi.org/10.48550/arXiv.2211.07060
chicago: Keszthelyi, Z., A. de Koter, Ylva Louise Linsdotter Götberg, G. Meynet,
S. A. Brands, V. Petit, M. Carrington, et al. “Spin-down and Reduced Mass Loss
in Early-Type Stars with Large-Scale Magnetic Fields.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2211.07060.
ieee: Z. Keszthelyi et al., “Spin-down and reduced mass loss in early-type
stars with large-scale magnetic fields,” arXiv. .
ista: Keszthelyi Z, Koter A de, Götberg YLL, Meynet G, Brands SA, Petit V, Carrington
M, A. David-Uraz AD-U, Geen ST, Georgy C, Hirschi R, Puls J, Ramalatswa KJ, Shultz
ME, A. ud-Doula A ud-Doula. Spin-down and reduced mass loss in early-type stars
with large-scale magnetic fields. arXiv, 2211.07060.
mla: Keszthelyi, Z., et al. “Spin-down and Reduced Mass Loss in Early-Type Stars
with Large-Scale Magnetic Fields.” ArXiv, 2211.07060, doi:10.48550/arXiv.2211.07060.
short: Z. Keszthelyi, A. de Koter, Y.L.L. Götberg, G. Meynet, S.A. Brands, V. Petit,
M. Carrington, A.D.-U. A. David-Uraz, S.T. Geen, C. Georgy, R. Hirschi, J. Puls,
K.J. Ramalatswa, M.E. Shultz, A. ud-Doula A. ud-Doula, ArXiv (n.d.).
date_created: 2023-08-21T10:11:37Z
date_published: 2022-11-14T00:00:00Z
date_updated: 2023-08-22T13:20:15Z
day: '14'
doi: 10.48550/arXiv.2211.07060
extern: '1'
external_id:
arxiv:
- '2211.07060'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2211.07060
month: '11'
oa: 1
oa_version: Submitted Version
publication: arXiv
publication_status: submitted
status: public
title: Spin-down and reduced mass loss in early-type stars with large-scale magnetic
fields
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '14106'
abstract:
- lang: eng
text: "We show that deep networks trained to satisfy demographic parity often do
so\r\nthrough a form of race or gender awareness, and that the more we force a
network\r\nto be fair, the more accurately we can recover race or gender from
the internal state\r\nof the network. Based on this observation, we investigate
an alternative fairness\r\napproach: we add a second classification head to the
network to explicitly predict\r\nthe protected attribute (such as race or gender)
alongside the original task. After\r\ntraining the two-headed network, we enforce
demographic parity by merging the\r\ntwo heads, creating a network with the same
architecture as the original network.\r\nWe establish a close relationship between
existing approaches and our approach\r\nby showing (1) that the decisions of a
fair classifier are well-approximated by our\r\napproach, and (2) that an unfair
and optimally accurate classifier can be recovered\r\nfrom a fair classifier and
our second head predicting the protected attribute. We use\r\nour explicit formulation
to argue that the existing fairness approaches, just as ours,\r\ndemonstrate disparate
treatment and that they are likely to be unlawful in a wide\r\nrange of scenarios
under US law."
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Michael
full_name: Lohaus, Michael
last_name: Lohaus
- first_name: Matthäus
full_name: Kleindessner, Matthäus
last_name: Kleindessner
- first_name: Krishnaram
full_name: Kenthapadi, Krishnaram
last_name: Kenthapadi
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Chris
full_name: Russell, Chris
last_name: Russell
citation:
ama: 'Lohaus M, Kleindessner M, Kenthapadi K, Locatello F, Russell C. Are two heads
the same as one? Identifying disparate treatment in fair neural networks. In:
36th Conference on Neural Information Processing Systems. Vol 35. Neural
Information Processing Systems Foundation; 2022:16548-16562.'
apa: 'Lohaus, M., Kleindessner, M., Kenthapadi, K., Locatello, F., & Russell,
C. (2022). Are two heads the same as one? Identifying disparate treatment in fair
neural networks. In 36th Conference on Neural Information Processing Systems
(Vol. 35, pp. 16548–16562). New Orleans, LA, United States: Neural Information
Processing Systems Foundation.'
chicago: Lohaus, Michael, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco
Locatello, and Chris Russell. “Are Two Heads the Same as One? Identifying Disparate
Treatment in Fair Neural Networks.” In 36th Conference on Neural Information
Processing Systems, 35:16548–62. Neural Information Processing Systems Foundation,
2022.
ieee: M. Lohaus, M. Kleindessner, K. Kenthapadi, F. Locatello, and C. Russell, “Are
two heads the same as one? Identifying disparate treatment in fair neural networks,”
in 36th Conference on Neural Information Processing Systems, New Orleans,
LA, United States, 2022, vol. 35, pp. 16548–16562.
ista: 'Lohaus M, Kleindessner M, Kenthapadi K, Locatello F, Russell C. 2022. Are
two heads the same as one? Identifying disparate treatment in fair neural networks.
36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information
Processing Systems, Advances in Neural Information Processing Systems, vol. 35,
16548–16562.'
mla: Lohaus, Michael, et al. “Are Two Heads the Same as One? Identifying Disparate
Treatment in Fair Neural Networks.” 36th Conference on Neural Information Processing
Systems, vol. 35, Neural Information Processing Systems Foundation, 2022,
pp. 16548–62.
short: M. Lohaus, M. Kleindessner, K. Kenthapadi, F. Locatello, C. Russell, in:,
36th Conference on Neural Information Processing Systems, Neural Information Processing
Systems Foundation, 2022, pp. 16548–16562.
conference:
end_date: 2022-12-09
location: New Orleans, LA, United States
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2022-11-28
date_created: 2023-08-21T12:12:42Z
date_published: 2022-12-15T00:00:00Z
date_updated: 2023-09-06T10:29:42Z
day: '15'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2204.04440'
intvolume: ' 35'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2204.04440
month: '12'
oa: 1
oa_version: Preprint
page: 16548-16562
publication: 36th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713871088'
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: Are two heads the same as one? Identifying disparate treatment in fair neural
networks
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2022'
...
---
_id: '14107'
abstract:
- lang: eng
text: "Amodal perception requires inferring the full shape of an object that is
partially occluded. This task is particularly challenging on two levels: (1) it
requires more information than what is contained in the instant retina or imaging
sensor, (2) it is difficult to obtain enough well-annotated amodal labels for
supervision. To this end, this paper develops a new framework of\r\nSelf-supervised
amodal Video object segmentation (SaVos). Our method efficiently leverages the
visual information of video temporal sequences to infer the amodal mask of objects.
The key intuition is that the occluded part of an object can be explained away
if that part is visible in other frames, possibly deformed as long as the deformation
can be reasonably learned.\r\nAccordingly, we derive a novel self-supervised learning
paradigm that efficiently utilizes the visible object parts as the supervision
to guide the training on videos. In addition to learning type prior to complete
masks for known types, SaVos also learns the spatiotemporal prior, which is also
useful for the amodal task and could generalize to unseen types. The proposed\r\nframework
achieves the state-of-the-art performance on the synthetic amodal segmentation
benchmark FISHBOWL and the real world benchmark KINS-Video-Car. Further, it lends
itself well to being transferred to novel distributions using test-time adaptation,
outperforming existing models even after the transfer to a new distribution."
article_processing_charge: No
arxiv: 1
author:
- first_name: Jian
full_name: Yao, Jian
last_name: Yao
- first_name: Yuxin
full_name: Hong, Yuxin
last_name: Hong
- first_name: Chiyu
full_name: Wang, Chiyu
last_name: Wang
- first_name: Tianjun
full_name: Xiao, Tianjun
last_name: Xiao
- first_name: Tong
full_name: He, Tong
last_name: He
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: David
full_name: Wipf, David
last_name: Wipf
- first_name: Yanwei
full_name: Fu, Yanwei
last_name: Fu
- first_name: Zheng
full_name: Zhang, Zheng
last_name: Zhang
citation:
ama: 'Yao J, Hong Y, Wang C, et al. Self-supervised amodal video object segmentation.
In: 36th Conference on Neural Information Processing Systems. ; 2022. doi:10.48550/arXiv.2210.12733'
apa: Yao, J., Hong, Y., Wang, C., Xiao, T., He, T., Locatello, F., … Zhang, Z. (2022).
Self-supervised amodal video object segmentation. In 36th Conference on Neural
Information Processing Systems. New Orleans, LA, United States. https://doi.org/10.48550/arXiv.2210.12733
chicago: Yao, Jian, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello,
David Wipf, Yanwei Fu, and Zheng Zhang. “Self-Supervised Amodal Video Object Segmentation.”
In 36th Conference on Neural Information Processing Systems, 2022. https://doi.org/10.48550/arXiv.2210.12733.
ieee: J. Yao et al., “Self-supervised amodal video object segmentation,”
in 36th Conference on Neural Information Processing Systems, New Orleans,
LA, United States, 2022.
ista: 'Yao J, Hong Y, Wang C, Xiao T, He T, Locatello F, Wipf D, Fu Y, Zhang Z.
2022. Self-supervised amodal video object segmentation. 36th Conference on Neural
Information Processing Systems. NeurIPS: Neural Information Processing Systems.'
mla: Yao, Jian, et al. “Self-Supervised Amodal Video Object Segmentation.” 36th
Conference on Neural Information Processing Systems, 2022, doi:10.48550/arXiv.2210.12733.
short: J. Yao, Y. Hong, C. Wang, T. Xiao, T. He, F. Locatello, D. Wipf, Y. Fu, Z.
Zhang, in:, 36th Conference on Neural Information Processing Systems, 2022.
conference:
end_date: 2022-12-01
location: New Orleans, LA, United States
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2022-11-28
date_created: 2023-08-21T12:13:25Z
date_published: 2022-10-23T00:00:00Z
date_updated: 2023-09-11T09:34:17Z
day: '23'
department:
- _id: FrLo
doi: 10.48550/arXiv.2210.12733
extern: '1'
external_id:
arxiv:
- '2210.12733'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2210.12733
month: '10'
oa: 1
oa_version: Preprint
publication: 36th Conference on Neural Information Processing Systems
publication_status: published
status: public
title: Self-supervised amodal video object segmentation
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '14114'
abstract:
- lang: eng
text: Algorithmic fairness is frequently motivated in terms of a trade-off in which
overall performance is decreased so as to improve performance on disadvantaged
groups where the algorithm would otherwise be less accurate. Contrary to this,
we find that applying existing fairness approaches to computer vision improve
fairness by degrading the performance of classifiers across all groups (with increased
degradation on the best performing groups). Extending the bias-variance decomposition
for classification to fairness, we theoretically explain why the majority of fairness
methods designed for low capacity models should not be used in settings involving
high-capacity models, a scenario common to computer vision. We corroborate this
analysis with extensive experimental support that shows that many of the fairness
heuristics used in computer vision also degrade performance on the most disadvantaged
groups. Building on these insights, we propose an adaptive augmentation strategy
that, uniquely, of all methods tested, improves performance for the disadvantaged
groups.
article_processing_charge: No
arxiv: 1
author:
- first_name: Dominik
full_name: Zietlow, Dominik
last_name: Zietlow
- first_name: Michael
full_name: Lohaus, Michael
last_name: Lohaus
- first_name: Guha
full_name: Balakrishnan, Guha
last_name: Balakrishnan
- first_name: Matthaus
full_name: Kleindessner, Matthaus
last_name: Kleindessner
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Bernhard
full_name: Scholkopf, Bernhard
last_name: Scholkopf
- first_name: Chris
full_name: Russell, Chris
last_name: Russell
citation:
ama: 'Zietlow D, Lohaus M, Balakrishnan G, et al. Leveling down in computer vision:
Pareto inefficiencies in fair deep classifiers. In: 2022 IEEE/CVF Conference
on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics
Engineers; 2022:10400-10411. doi:10.1109/cvpr52688.2022.01016'
apa: 'Zietlow, D., Lohaus, M., Balakrishnan, G., Kleindessner, M., Locatello, F.,
Scholkopf, B., & Russell, C. (2022). Leveling down in computer vision: Pareto
inefficiencies in fair deep classifiers. In 2022 IEEE/CVF Conference on Computer
Vision and Pattern Recognition (pp. 10400–10411). New Orleans, LA, United
States: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/cvpr52688.2022.01016'
chicago: 'Zietlow, Dominik, Michael Lohaus, Guha Balakrishnan, Matthaus Kleindessner,
Francesco Locatello, Bernhard Scholkopf, and Chris Russell. “Leveling down in
Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers.” In 2022 IEEE/CVF
Conference on Computer Vision and Pattern Recognition, 10400–411. Institute
of Electrical and Electronics Engineers, 2022. https://doi.org/10.1109/cvpr52688.2022.01016.'
ieee: 'D. Zietlow et al., “Leveling down in computer vision: Pareto inefficiencies
in fair deep classifiers,” in 2022 IEEE/CVF Conference on Computer Vision and
Pattern Recognition, New Orleans, LA, United States, 2022, pp. 10400–10411.'
ista: 'Zietlow D, Lohaus M, Balakrishnan G, Kleindessner M, Locatello F, Scholkopf
B, Russell C. 2022. Leveling down in computer vision: Pareto inefficiencies in
fair deep classifiers. 2022 IEEE/CVF Conference on Computer Vision and Pattern
Recognition. CVPR: Conference on Computer Vision and Pattern Recognition, 10400–10411.'
mla: 'Zietlow, Dominik, et al. “Leveling down in Computer Vision: Pareto Inefficiencies
in Fair Deep Classifiers.” 2022 IEEE/CVF Conference on Computer Vision and
Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022,
pp. 10400–11, doi:10.1109/cvpr52688.2022.01016.'
short: D. Zietlow, M. Lohaus, G. Balakrishnan, M. Kleindessner, F. Locatello, B.
Scholkopf, C. Russell, in:, 2022 IEEE/CVF Conference on Computer Vision and Pattern
Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 10400–10411.
conference:
end_date: 2022-06-24
location: New Orleans, LA, United States
name: 'CVPR: Conference on Computer Vision and Pattern Recognition'
start_date: 2022-06-18
date_created: 2023-08-21T12:18:00Z
date_published: 2022-07-01T00:00:00Z
date_updated: 2023-09-11T09:19:14Z
day: '01'
department:
- _id: FrLo
doi: 10.1109/cvpr52688.2022.01016
extern: '1'
external_id:
arxiv:
- '2203.04913'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2203.04913
month: '07'
oa: 1
oa_version: Preprint
page: 10400-10411
publication: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition
publication_identifier:
eissn:
- 2575-7075
isbn:
- '9781665469470'
issn:
- 1063-6919
publication_status: published
publisher: Institute of Electrical and Electronics Engineers
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Leveling down in computer vision: Pareto inefficiencies in fair deep classifiers'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '14168'
abstract:
- lang: eng
text: "Recent work has seen the development of general purpose neural architectures\r\nthat
can be trained to perform tasks across diverse data modalities. General\r\npurpose
models typically make few assumptions about the underlying\r\ndata-structure and
are known to perform well in the large-data regime. At the\r\nsame time, there
has been growing interest in modular neural architectures that\r\nrepresent the
data using sparsely interacting modules. These models can be more\r\nrobust out-of-distribution,
computationally efficient, and capable of\r\nsample-efficient adaptation to new
data. However, they tend to make\r\ndomain-specific assumptions about the data,
and present challenges in how\r\nmodule behavior (i.e., parameterization) and
connectivity (i.e., their layout)\r\ncan be jointly learned. In this work, we
introduce a general purpose, yet\r\nmodular neural architecture called Neural
Attentive Circuits (NACs) that\r\njointly learns the parameterization and a sparse
connectivity of neural modules\r\nwithout using domain knowledge. NACs are best
understood as the combination of\r\ntwo systems that are jointly trained end-to-end:
one that determines the module\r\nconfiguration and the other that executes it
on an input. We demonstrate\r\nqualitatively that NACs learn diverse and meaningful
module configurations on\r\nthe NLVR2 dataset without additional supervision.
Quantitatively, we show that\r\nby incorporating modularity in this way, NACs
improve upon a strong non-modular\r\nbaseline in terms of low-shot adaptation
on CIFAR and CUBs dataset by about\r\n10%, and OOD robustness on Tiny ImageNet-R
by about 2.5%. Further, we find that\r\nNACs can achieve an 8x speedup at inference
time while losing less than 3%\r\nperformance. Finally, we find NACs to yield
competitive results on diverse data\r\nmodalities spanning point-cloud classification,
symbolic processing and\r\ntext-classification from ASCII bytes, thereby confirming
its general purpose\r\nnature."
alternative_title:
- ' Advances in Neural Information Processing Systems'
article_processing_charge: No
arxiv: 1
author:
- first_name: Nasim
full_name: Rahaman, Nasim
last_name: Rahaman
- first_name: Martin
full_name: Weiss, Martin
last_name: Weiss
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Chris
full_name: Pal, Chris
last_name: Pal
- first_name: Yoshua
full_name: Bengio, Yoshua
last_name: Bengio
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Li Erran
full_name: Li, Li Erran
last_name: Li
- first_name: Nicolas
full_name: Ballas, Nicolas
last_name: Ballas
citation:
ama: 'Rahaman N, Weiss M, Locatello F, et al. Neural attentive circuits. In: 36th
Conference on Neural Information Processing Systems. Vol 35. ; 2022.'
apa: Rahaman, N., Weiss, M., Locatello, F., Pal, C., Bengio, Y., Schölkopf, B.,
… Ballas, N. (2022). Neural attentive circuits. In 36th Conference on Neural
Information Processing Systems (Vol. 35). New Orleans, United States.
chicago: Rahaman, Nasim, Martin Weiss, Francesco Locatello, Chris Pal, Yoshua Bengio,
Bernhard Schölkopf, Li Erran Li, and Nicolas Ballas. “Neural Attentive Circuits.”
In 36th Conference on Neural Information Processing Systems, Vol. 35, 2022.
ieee: N. Rahaman et al., “Neural attentive circuits,” in 36th Conference
on Neural Information Processing Systems, New Orleans, United States, 2022,
vol. 35.
ista: 'Rahaman N, Weiss M, Locatello F, Pal C, Bengio Y, Schölkopf B, Li LE, Ballas
N. 2022. Neural attentive circuits. 36th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information
Processing Systems, vol. 35.'
mla: Rahaman, Nasim, et al. “Neural Attentive Circuits.” 36th Conference on Neural
Information Processing Systems, vol. 35, 2022.
short: N. Rahaman, M. Weiss, F. Locatello, C. Pal, Y. Bengio, B. Schölkopf, L.E.
Li, N. Ballas, in:, 36th Conference on Neural Information Processing Systems,
2022.
conference:
end_date: 2022-12-01
location: New Orleans, United States
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2022-11-29
date_created: 2023-08-22T13:57:27Z
date_published: 2022-10-14T00:00:00Z
date_updated: 2023-09-11T09:29:09Z
day: '14'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2210.08031'
intvolume: ' 35'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2210.08031
month: '10'
oa: 1
oa_version: Preprint
publication: 36th Conference on Neural Information Processing Systems
publication_status: published
status: public
title: Neural attentive circuits
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2022'
...
---
_id: '14170'
abstract:
- lang: eng
text: "The idea behind object-centric representation learning is that natural scenes
can better be modeled as compositions of objects and their relations as opposed
to distributed representations. This inductive bias can be injected into neural
networks to potentially improve systematic generalization and performance of downstream
tasks in scenes with multiple objects. In this paper, we train state-of-the-art
unsupervised models on five common multi-object datasets and evaluate segmentation
metrics and downstream object property prediction. In addition, we study generalization
and robustness by investigating the settings where either a single object is out
of distribution -- e.g., having an unseen color, texture, or shape -- or global
properties of the scene are altered -- e.g., by occlusions, cropping, or increasing
the number of objects. From our experimental study, we find object-centric representations
to be useful for\r\ndownstream tasks and generally robust to most distribution
shifts affecting objects. However, when the distribution shift affects the input
in a less structured manner, robustness in terms of segmentation and downstream
task performance may vary significantly across models and distribution shifts. "
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Andrea
full_name: Dittadi, Andrea
last_name: Dittadi
- first_name: Samuele
full_name: Papa, Samuele
last_name: Papa
- first_name: Michele De
full_name: Vita, Michele De
last_name: Vita
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Ole
full_name: Winther, Ole
last_name: Winther
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: 'Dittadi A, Papa S, Vita MD, Schölkopf B, Winther O, Locatello F. Generalization
and robustness implications in object-centric learning. In: Proceedings of
the 39th International Conference on Machine Learning. Vol 2022. ML Research
Press; :5221-5285.'
apa: 'Dittadi, A., Papa, S., Vita, M. D., Schölkopf, B., Winther, O., & Locatello,
F. (n.d.). Generalization and robustness implications in object-centric learning.
In Proceedings of the 39th International Conference on Machine Learning
(Vol. 2022, pp. 5221–5285). Baltimore, MD, United States: ML Research Press.'
chicago: Dittadi, Andrea, Samuele Papa, Michele De Vita, Bernhard Schölkopf, Ole
Winther, and Francesco Locatello. “Generalization and Robustness Implications
in Object-Centric Learning.” In Proceedings of the 39th International Conference
on Machine Learning, 2022:5221–85. ML Research Press, n.d.
ieee: A. Dittadi, S. Papa, M. D. Vita, B. Schölkopf, O. Winther, and F. Locatello,
“Generalization and robustness implications in object-centric learning,” in Proceedings
of the 39th International Conference on Machine Learning, Baltimore, MD, United
States, vol. 2022, pp. 5221–5285.
ista: Dittadi A, Papa S, Vita MD, Schölkopf B, Winther O, Locatello F. Generalization
and robustness implications in object-centric learning. Proceedings of the 39th
International Conference on Machine Learning. International Conference on Machine
Learning, PMLR, vol. 2022, 5221–5285.
mla: Dittadi, Andrea, et al. “Generalization and Robustness Implications in Object-Centric
Learning.” Proceedings of the 39th International Conference on Machine Learning,
vol. 2022, ML Research Press, pp. 5221–85.
short: A. Dittadi, S. Papa, M.D. Vita, B. Schölkopf, O. Winther, F. Locatello, in:,
Proceedings of the 39th International Conference on Machine Learning, ML Research
Press, n.d., pp. 5221–5285.
conference:
end_date: 2022-07-23
location: Baltimore, MD, United States
name: International Conference on Machine Learning
start_date: 2022-07-17
date_created: 2023-08-22T13:59:55Z
date_published: 2022-07-22T00:00:00Z
date_updated: 2023-09-11T10:08:14Z
day: '22'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2107.00637'
intvolume: ' 2022'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2107.00637
month: '07'
oa: 1
oa_version: Preprint
page: 5221-5285
publication: Proceedings of the 39th International Conference on Machine Learning
publication_status: submitted
publisher: ML Research Press
quality_controlled: '1'
status: public
title: Generalization and robustness implications in object-centric learning
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2022
year: '2022'
...
---
_id: '14171'
abstract:
- lang: eng
text: "This paper demonstrates how to recover causal graphs from the score of the\r\ndata
distribution in non-linear additive (Gaussian) noise models. Using score\r\nmatching
algorithms as a building block, we show how to design a new generation\r\nof scalable
causal discovery methods. To showcase our approach, we also propose\r\na new efficient
method for approximating the score's Jacobian, enabling to\r\nrecover the causal
graph. Empirically, we find that the new algorithm, called\r\nSCORE, is competitive
with state-of-the-art causal discovery methods while\r\nbeing significantly faster."
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Paul
full_name: Rolland, Paul
last_name: Rolland
- first_name: Volkan
full_name: Cevher, Volkan
last_name: Cevher
- first_name: Matthäus
full_name: Kleindessner, Matthäus
last_name: Kleindessner
- first_name: Chris
full_name: Russel, Chris
last_name: Russel
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Dominik
full_name: Janzing, Dominik
last_name: Janzing
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: 'Rolland P, Cevher V, Kleindessner M, et al. Score matching enables causal
discovery of nonlinear additive noise models. In: Proceedings of the 39th
International Conference on Machine Learning. Vol 162. ML Research Press;
2022:18741-18753.'
apa: 'Rolland, P., Cevher, V., Kleindessner, M., Russel, C., Schölkopf, B., Janzing,
D., & Locatello, F. (2022). Score matching enables causal discovery of nonlinear
additive noise models. In Proceedings of the 39th International Conference
on Machine Learning (Vol. 162, pp. 18741–18753). Baltimore, MD, United States:
ML Research Press.'
chicago: Rolland, Paul, Volkan Cevher, Matthäus Kleindessner, Chris Russel, Bernhard
Schölkopf, Dominik Janzing, and Francesco Locatello. “Score Matching Enables Causal
Discovery of Nonlinear Additive Noise Models.” In Proceedings of the 39th
International Conference on Machine Learning, 162:18741–53. ML Research Press,
2022.
ieee: P. Rolland et al., “Score matching enables causal discovery of nonlinear
additive noise models,” in Proceedings of the 39th International Conference
on Machine Learning, Baltimore, MD, United States, 2022, vol. 162, pp. 18741–18753.
ista: Rolland P, Cevher V, Kleindessner M, Russel C, Schölkopf B, Janzing D, Locatello
F. 2022. Score matching enables causal discovery of nonlinear additive noise
models. Proceedings of the 39th International Conference on Machine Learning.
International Conference on Machine Learning, PMLR, vol. 162, 18741–18753.
mla: Rolland, Paul, et al. “Score Matching Enables Causal Discovery of Nonlinear
Additive Noise Models.” Proceedings of the 39th International Conference on
Machine Learning, vol. 162, ML Research Press, 2022, pp. 18741–53.
short: P. Rolland, V. Cevher, M. Kleindessner, C. Russel, B. Schölkopf, D. Janzing,
F. Locatello, in:, Proceedings of the 39th International Conference on Machine
Learning, ML Research Press, 2022, pp. 18741–18753.
conference:
end_date: 2022-07-23
location: Baltimore, MD, United States
name: International Conference on Machine Learning
start_date: 2022-07-17
date_created: 2023-08-22T14:00:18Z
date_published: 2022-07-22T00:00:00Z
date_updated: 2023-09-11T10:14:20Z
day: '22'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2203.04413'
intvolume: ' 162'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2203.04413
month: '07'
oa: 1
oa_version: Preprint
page: 18741-18753
publication: Proceedings of the 39th International Conference on Machine Learning
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
status: public
title: Score matching enables causal discovery of nonlinear additive noise models
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 162
year: '2022'
...
---
_id: '14172'
abstract:
- lang: eng
text: "An important component for generalization in machine learning is to uncover
underlying latent factors of variation as well as the mechanism through which
each factor acts in the world. In this paper, we test whether 17 unsupervised,
weakly supervised, and fully supervised representation learning approaches correctly
infer the generative factors of variation in simple datasets (dSprites, Shapes3D,
MPI3D) from controlled environments, and on our contributed CelebGlow dataset.
In contrast to prior robustness work that introduces novel factors of variation
during test time, such as blur or other (un)structured noise, we here recompose,
interpolate, or extrapolate only existing factors of variation from the training
data set (e.g., small and medium-sized objects during training and large objects
during testing). Models\r\nthat learn the correct mechanism should be able to
generalize to this benchmark. In total, we train and test 2000+ models and observe
that all of them struggle to learn the underlying mechanism regardless of supervision
signal and architectural bias. Moreover, the generalization capabilities of all
tested models drop significantly as we move from artificial datasets towards\r\nmore
realistic real-world datasets. Despite their inability to identify the correct
mechanism, the models are quite modular as their ability to infer other in-distribution
factors remains fairly stable, providing only a single factoris out-of-distribution.
These results point to an important yet understudied problem of learning mechanistic
models of observations that can facilitate\r\ngeneralization."
article_processing_charge: No
arxiv: 1
author:
- first_name: Lukas
full_name: Schott, Lukas
last_name: Schott
- first_name: Julius von
full_name: Kügelgen, Julius von
last_name: Kügelgen
- first_name: Frederik
full_name: Träuble, Frederik
last_name: Träuble
- first_name: Peter
full_name: Gehler, Peter
last_name: Gehler
- first_name: Chris
full_name: Russell, Chris
last_name: Russell
- first_name: Matthias
full_name: Bethge, Matthias
last_name: Bethge
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Wieland
full_name: Brendel, Wieland
last_name: Brendel
citation:
ama: 'Schott L, Kügelgen J von, Träuble F, et al. Visual representation learning
does not generalize strongly within the same domain. In: 10th International
Conference on Learning Representations. ; 2022.'
apa: Schott, L., Kügelgen, J. von, Träuble, F., Gehler, P., Russell, C., Bethge,
M., … Brendel, W. (2022). Visual representation learning does not generalize strongly
within the same domain. In 10th International Conference on Learning Representations.
Virtual.
chicago: Schott, Lukas, Julius von Kügelgen, Frederik Träuble, Peter Gehler, Chris
Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, and Wieland
Brendel. “Visual Representation Learning Does Not Generalize Strongly within the
Same Domain.” In 10th International Conference on Learning Representations,
2022.
ieee: L. Schott et al., “Visual representation learning does not generalize
strongly within the same domain,” in 10th International Conference on Learning
Representations, Virtual, 2022.
ista: 'Schott L, Kügelgen J von, Träuble F, Gehler P, Russell C, Bethge M, Schölkopf
B, Locatello F, Brendel W. 2022. Visual representation learning does not generalize
strongly within the same domain. 10th International Conference on Learning Representations.
ICLR: International Conference on Learning Representations.'
mla: Schott, Lukas, et al. “Visual Representation Learning Does Not Generalize Strongly
within the Same Domain.” 10th International Conference on Learning Representations,
2022.
short: L. Schott, J. von Kügelgen, F. Träuble, P. Gehler, C. Russell, M. Bethge,
B. Schölkopf, F. Locatello, W. Brendel, in:, 10th International Conference on
Learning Representations, 2022.
conference:
end_date: 2022-04-29
location: Virtual
name: 'ICLR: International Conference on Learning Representations'
start_date: 2022-04-25
date_created: 2023-08-22T14:00:50Z
date_published: 2022-04-25T00:00:00Z
date_updated: 2023-09-11T09:40:52Z
day: '25'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2107.08221'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2107.08221
month: '04'
oa: 1
oa_version: Preprint
publication: 10th International Conference on Learning Representations
publication_status: published
quality_controlled: '1'
status: public
title: Visual representation learning does not generalize strongly within the same
domain
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '14173'
abstract:
- lang: eng
text: "Since out-of-distribution generalization is a generally ill-posed problem,
various proxy targets (e.g., calibration, adversarial robustness, algorithmic
corruptions, invariance across shifts) were studied across different research
programs resulting in different recommendations. While sharing the same aspirational
goal, these approaches have never been tested under the same\r\nexperimental conditions
on real data. In this paper, we take a unified view of previous work, highlighting
message discrepancies that we address empirically, and providing recommendations
on how to measure the robustness of a model and how to improve it. To this end,
we collect 172 publicly available dataset pairs for training and out-of-distribution
evaluation of accuracy, calibration error, adversarial attacks, environment invariance,
and synthetic corruptions. We fine-tune over 31k networks, from nine different
architectures in the many- and\r\nfew-shot setting. Our findings confirm that
in- and out-of-distribution accuracies tend to increase jointly, but show that
their relation is largely dataset-dependent, and in general more nuanced and more
complex than posited by previous, smaller scale studies."
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Florian
full_name: Wenzel, Florian
last_name: Wenzel
- first_name: Andrea
full_name: Dittadi, Andrea
last_name: Dittadi
- first_name: Peter Vincent
full_name: Gehler, Peter Vincent
last_name: Gehler
- first_name: Carl-Johann Simon-Gabriel
full_name: Carl-Johann Simon-Gabriel, Carl-Johann Simon-Gabriel
last_name: Carl-Johann Simon-Gabriel
- first_name: Max
full_name: Horn, Max
last_name: Horn
- first_name: Dominik
full_name: Zietlow, Dominik
last_name: Zietlow
- first_name: David
full_name: Kernert, David
last_name: Kernert
- first_name: Chris
full_name: Russell, Chris
last_name: Russell
- first_name: Thomas
full_name: Brox, Thomas
last_name: Brox
- first_name: Bernt
full_name: Schiele, Bernt
last_name: Schiele
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: 'Wenzel F, Dittadi A, Gehler PV, et al. Assaying out-of-distribution generalization
in transfer learning. In: 36th Conference on Neural Information Processing
Systems. Vol 35. Neural Information Processing Systems Foundation; 2022:7181-7198.'
apa: 'Wenzel, F., Dittadi, A., Gehler, P. V., Carl-Johann Simon-Gabriel, C.-J. S.-G.,
Horn, M., Zietlow, D., … Locatello, F. (2022). Assaying out-of-distribution generalization
in transfer learning. In 36th Conference on Neural Information Processing Systems
(Vol. 35, pp. 7181–7198). New Orleans, LA, United States: Neural Information Processing
Systems Foundation.'
chicago: Wenzel, Florian, Andrea Dittadi, Peter Vincent Gehler, Carl-Johann Simon-Gabriel
Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, et al. “Assaying
Out-of-Distribution Generalization in Transfer Learning.” In 36th Conference
on Neural Information Processing Systems, 35:7181–98. Neural Information Processing
Systems Foundation, 2022.
ieee: F. Wenzel et al., “Assaying out-of-distribution generalization in transfer
learning,” in 36th Conference on Neural Information Processing Systems,
New Orleans, LA, United States, 2022, vol. 35, pp. 7181–7198.
ista: 'Wenzel F, Dittadi A, Gehler PV, Carl-Johann Simon-Gabriel C-JS-G, Horn M,
Zietlow D, Kernert D, Russell C, Brox T, Schiele B, Schölkopf B, Locatello F.
2022. Assaying out-of-distribution generalization in transfer learning. 36th Conference
on Neural Information Processing Systems. NeurIPS: Neural Information Processing
Systems, Advances in Neural Information Processing Systems, vol. 35, 7181–7198.'
mla: Wenzel, Florian, et al. “Assaying Out-of-Distribution Generalization in Transfer
Learning.” 36th Conference on Neural Information Processing Systems, vol.
35, Neural Information Processing Systems Foundation, 2022, pp. 7181–98.
short: F. Wenzel, A. Dittadi, P.V. Gehler, C.-J.S.-G. Carl-Johann Simon-Gabriel,
M. Horn, D. Zietlow, D. Kernert, C. Russell, T. Brox, B. Schiele, B. Schölkopf,
F. Locatello, in:, 36th Conference on Neural Information Processing Systems, Neural
Information Processing Systems Foundation, 2022, pp. 7181–7198.
conference:
end_date: 2022-12-09
location: New Orleans, LA, United States
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2022-11-28
date_created: 2023-08-22T14:01:13Z
date_published: 2022-12-15T00:00:00Z
date_updated: 2023-09-06T10:34:43Z
day: '15'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2207.09239'
intvolume: ' 35'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2207.09239
month: '12'
oa: 1
oa_version: Preprint
page: 7181-7198
publication: 36th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713871088'
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: Assaying out-of-distribution generalization in transfer learning
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2022'
...