---
_id: '11463'
abstract:
- lang: eng
text: "Efficiently approximating local curvature information of the loss function
is a key tool for optimization and compression of deep neural networks. Yet, most
existing methods to approximate second-order information have high computational\r\nor
storage costs, which limits their practicality. In this work, we investigate matrix-free,
linear-time approaches for estimating Inverse-Hessian Vector Products (IHVPs)
for the case when the Hessian can be approximated as a sum of rank-one matrices,
as in the classic approximation of the Hessian by the empirical Fisher matrix.
We propose two new algorithms: the first is tailored towards network compression
and can compute the IHVP for dimension d, if the Hessian is given as a sum of
m rank-one matrices, using O(dm2) precomputation, O(dm) cost for computing the
IHVP, and query cost O(m) for any single element of the inverse Hessian. The second
algorithm targets an optimization setting, where we wish to compute the product
between the inverse Hessian, estimated over a sliding window of optimization steps,
and a given gradient direction, as required for preconditioned SGD. We give an
algorithm with cost O(dm + m2) for computing the IHVP and O(dm + m3) for adding
or removing any gradient from the sliding window. These\r\ntwo algorithms yield
state-of-the-art results for network pruning and optimization with lower computational
overhead relative to existing second-order methods. Implementations are available
at [9] and [17]."
acknowledgement: We gratefully acknowledge funding the European Research Council (ERC)
under the European Union’s Horizon 2020 research and innovation programme (grant
agreement No 805223 ScaleML), as well as computational support from Amazon Web Services
(AWS) EC2.
article_processing_charge: No
arxiv: 1
author:
- first_name: Elias
full_name: Frantar, Elias
id: 09a8f98d-ec99-11ea-ae11-c063a7b7fe5f
last_name: Frantar
- first_name: Eldar
full_name: Kurtic, Eldar
id: 47beb3a5-07b5-11eb-9b87-b108ec578218
last_name: Kurtic
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Frantar E, Kurtic E, Alistarh D-A. M-FAC: Efficient matrix-free approximations
of second-order information. In: 35th Conference on Neural Information Processing
Systems. Vol 34. Curran Associates; 2021:14873-14886.'
apa: 'Frantar, E., Kurtic, E., & Alistarh, D.-A. (2021). M-FAC: Efficient matrix-free
approximations of second-order information. In 35th Conference on Neural Information
Processing Systems (Vol. 34, pp. 14873–14886). Virtual, Online: Curran Associates.'
chicago: 'Frantar, Elias, Eldar Kurtic, and Dan-Adrian Alistarh. “M-FAC: Efficient
Matrix-Free Approximations of Second-Order Information.” In 35th Conference
on Neural Information Processing Systems, 34:14873–86. Curran Associates,
2021.'
ieee: 'E. Frantar, E. Kurtic, and D.-A. Alistarh, “M-FAC: Efficient matrix-free
approximations of second-order information,” in 35th Conference on Neural Information
Processing Systems, Virtual, Online, 2021, vol. 34, pp. 14873–14886.'
ista: 'Frantar E, Kurtic E, Alistarh D-A. 2021. M-FAC: Efficient matrix-free approximations
of second-order information. 35th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems vol. 34, 14873–14886.'
mla: 'Frantar, Elias, et al. “M-FAC: Efficient Matrix-Free Approximations of Second-Order
Information.” 35th Conference on Neural Information Processing Systems,
vol. 34, Curran Associates, 2021, pp. 14873–86.'
short: E. Frantar, E. Kurtic, D.-A. Alistarh, in:, 35th Conference on Neural Information
Processing Systems, Curran Associates, 2021, pp. 14873–14886.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-26T22:01:35Z
date_published: 2021-12-06T00:00:00Z
date_updated: 2022-06-27T07:05:12Z
day: '06'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2010.08222'
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/7cfd5df443b4eb0d69886a583b33de4c-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 14873-14886
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: 35th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'M-FAC: Efficient matrix-free approximations of second-order information'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
_id: '11464'
abstract:
- lang: eng
text: "We consider a standard distributed optimisation setting where N machines,
each holding a d-dimensional function\r\nfi, aim to jointly minimise the sum of
the functions ∑Ni=1fi(x). This problem arises naturally in large-scale distributed
optimisation, where a standard solution is to apply variants of (stochastic) gradient
descent. We focus on the communication complexity of this problem: our main result
provides the first fully unconditional bounds on total number of bits which need
to be sent and received by the N machines to solve this problem under point-to-point
communication, within a given error-tolerance. Specifically, we show that Ω(Ndlogd/Nε)
total bits need to be communicated between the machines to find an additive ϵ-approximation
to the minimum of ∑Ni=1fi(x). The result holds for both deterministic and randomised
algorithms, and, importantly, requires no assumptions on the algorithm structure.
The lower bound is tight under certain restrictions on parameter values, and is
matched within constant factors for quadratic objectives by a new variant of quantised
gradient descent, which we describe and analyse. Our results bring over tools
from communication complexity to distributed optimisation, which has potential
for further applications."
acknowledgement: We thank the NeurIPS reviewers for insightful comments that helped
us improve the positioning of our results, as well as for pointing out the subsampling
approach for complementing the randomised lower bound. We also thank Foivos Alimisis
and Peter Davies for useful discussions. This project has received funding from
the European Research Council (ERC) under the European Union’s Horizon 2020 research
and innovation programme (grant agreement No 805223 ScaleML).
article_processing_charge: No
arxiv: 1
author:
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
- first_name: Janne
full_name: Korhonen, Janne
id: C5402D42-15BC-11E9-A202-CA2BE6697425
last_name: Korhonen
citation:
ama: 'Alistarh D-A, Korhonen J. Towards tight communication lower bounds for distributed
optimisation. In: 35th Conference on Neural Information Processing Systems.
Vol 34. Curran Associates; 2021:7254-7266.'
apa: 'Alistarh, D.-A., & Korhonen, J. (2021). Towards tight communication lower
bounds for distributed optimisation. In 35th Conference on Neural Information
Processing Systems (Vol. 34, pp. 7254–7266). Virtual, Online: Curran Associates.'
chicago: Alistarh, Dan-Adrian, and Janne Korhonen. “Towards Tight Communication
Lower Bounds for Distributed Optimisation.” In 35th Conference on Neural Information
Processing Systems, 34:7254–66. Curran Associates, 2021.
ieee: D.-A. Alistarh and J. Korhonen, “Towards tight communication lower bounds
for distributed optimisation,” in 35th Conference on Neural Information Processing
Systems, Virtual, Online, 2021, vol. 34, pp. 7254–7266.
ista: 'Alistarh D-A, Korhonen J. 2021. Towards tight communication lower bounds
for distributed optimisation. 35th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems vol. 34, 7254–7266.'
mla: Alistarh, Dan-Adrian, and Janne Korhonen. “Towards Tight Communication Lower
Bounds for Distributed Optimisation.” 35th Conference on Neural Information
Processing Systems, vol. 34, Curran Associates, 2021, pp. 7254–66.
short: D.-A. Alistarh, J. Korhonen, in:, 35th Conference on Neural Information Processing
Systems, Curran Associates, 2021, pp. 7254–7266.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-26T22:01:35Z
date_published: 2021-12-06T00:00:00Z
date_updated: 2022-06-27T06:54:31Z
day: '06'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2010.08222'
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/3b92d18aa7a6176dd37d372bc2f1eb71-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 7254-7266
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: 35th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
scopus_import: '1'
status: public
title: Towards tight communication lower bounds for distributed optimisation
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
_id: '7883'
abstract:
- lang: eng
text: All vertebrates have a spinal cord with dimensions and shape specific to their
species. Yet how species‐specific organ size and shape are achieved is a fundamental
unresolved question in biology. The formation and sculpting of organs begins during
embryonic development. As it develops, the spinal cord extends in anterior–posterior
direction in synchrony with the overall growth of the body. The dorsoventral (DV)
and apicobasal lengths of the spinal cord neuroepithelium also change, while at
the same time a characteristic pattern of neural progenitor subtypes along the
DV axis is established and elaborated. At the basis of these changes in tissue
size and shape are biophysical determinants, such as the change in cell number,
cell size and shape, and anisotropic tissue growth. These processes are controlled
by global tissue‐scale regulators, such as morphogen signaling gradients as well
as mechanical forces. Current challenges in the field are to uncover how these
tissue‐scale regulatory mechanisms are translated to the cellular and molecular
level, and how regulation of distinct cellular processes gives rise to an overall
defined size. Addressing these questions will help not only to achieve a better
understanding of how size is controlled, but also of how tissue size is coordinated
with the specification of pattern.
acknowledgement: 'Austrian Academy of Sciences, Grant/Award Number: DOC fellowship
for Katarzyna Kuzmicz-Kowalska; Austrian Science Fund, Grant/Award Number: F78 (Stem
Cell Modulation); H2020 European Research Council, Grant/Award Number: 680037'
article_number: e383
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Katarzyna
full_name: Kuzmicz-Kowalska, Katarzyna
id: 4CED352A-F248-11E8-B48F-1D18A9856A87
last_name: Kuzmicz-Kowalska
- first_name: Anna
full_name: Kicheva, Anna
id: 3959A2A0-F248-11E8-B48F-1D18A9856A87
last_name: Kicheva
orcid: 0000-0003-4509-4998
citation:
ama: 'Kuzmicz-Kowalska K, Kicheva A. Regulation of size and scale in vertebrate
spinal cord development. Wiley Interdisciplinary Reviews: Developmental Biology.
2021. doi:10.1002/wdev.383'
apa: 'Kuzmicz-Kowalska, K., & Kicheva, A. (2021). Regulation of size and scale
in vertebrate spinal cord development. Wiley Interdisciplinary Reviews: Developmental
Biology. Wiley. https://doi.org/10.1002/wdev.383'
chicago: 'Kuzmicz-Kowalska, Katarzyna, and Anna Kicheva. “Regulation of Size and
Scale in Vertebrate Spinal Cord Development.” Wiley Interdisciplinary Reviews:
Developmental Biology. Wiley, 2021. https://doi.org/10.1002/wdev.383.'
ieee: 'K. Kuzmicz-Kowalska and A. Kicheva, “Regulation of size and scale in vertebrate
spinal cord development,” Wiley Interdisciplinary Reviews: Developmental Biology.
Wiley, 2021.'
ista: 'Kuzmicz-Kowalska K, Kicheva A. 2021. Regulation of size and scale in vertebrate
spinal cord development. Wiley Interdisciplinary Reviews: Developmental Biology.,
e383.'
mla: 'Kuzmicz-Kowalska, Katarzyna, and Anna Kicheva. “Regulation of Size and Scale
in Vertebrate Spinal Cord Development.” Wiley Interdisciplinary Reviews: Developmental
Biology, e383, Wiley, 2021, doi:10.1002/wdev.383.'
short: 'K. Kuzmicz-Kowalska, A. Kicheva, Wiley Interdisciplinary Reviews: Developmental
Biology (2021).'
date_created: 2020-05-24T22:01:00Z
date_published: 2021-04-15T00:00:00Z
date_updated: 2024-03-07T15:03:00Z
day: '15'
ddc:
- '570'
department:
- _id: AnKi
doi: 10.1002/wdev.383
ec_funded: 1
external_id:
isi:
- '000531419400001'
pmid:
- '32391980'
file:
- access_level: open_access
checksum: f0a7745d48afa09ea7025e876a0145a8
content_type: application/pdf
creator: dernst
date_created: 2020-11-24T13:11:39Z
date_updated: 2020-11-24T13:11:39Z
file_id: '8800'
file_name: 2020_WIREs_DevBio_KuzmiczKowalska.pdf
file_size: 2527276
relation: main_file
success: 1
file_date_updated: 2020-11-24T13:11:39Z
has_accepted_license: '1'
isi: 1
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '04'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: B6FC0238-B512-11E9-945C-1524E6697425
call_identifier: H2020
grant_number: '680037'
name: Coordination of Patterning And Growth In the Spinal Cord
- _id: 267AF0E4-B435-11E9-9278-68D0E5697425
name: The role of morphogens in the regulation of neural tube growth
- _id: 059DF620-7A3F-11EA-A408-12923DDC885E
grant_number: F07802
name: Morphogen control of growth and pattern in the spinal cord
publication: 'Wiley Interdisciplinary Reviews: Developmental Biology'
publication_identifier:
eissn:
- '17597692'
issn:
- '17597684'
publication_status: published
publisher: Wiley
quality_controlled: '1'
related_material:
record:
- id: '14323'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Regulation of size and scale in vertebrate spinal cord development
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '7900'
abstract:
- lang: eng
text: Hartree–Fock theory has been justified as a mean-field approximation for fermionic
systems. However, it suffers from some defects in predicting physical properties,
making necessary a theory of quantum correlations. Recently, bosonization of many-body
correlations has been rigorously justified as an upper bound on the correlation
energy at high density with weak interactions. We review the bosonic approximation,
deriving an effective Hamiltonian. We then show that for systems with Coulomb
interaction this effective theory predicts collective excitations (plasmons) in
accordance with the random phase approximation of Bohm and Pines, and with experimental
observation.
article_number: '2060009'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Niels P
full_name: Benedikter, Niels P
id: 3DE6C32A-F248-11E8-B48F-1D18A9856A87
last_name: Benedikter
orcid: 0000-0002-1071-6091
citation:
ama: Benedikter NP. Bosonic collective excitations in Fermi gases. Reviews in
Mathematical Physics. 2021;33(1). doi:10.1142/s0129055x20600090
apa: Benedikter, N. P. (2021). Bosonic collective excitations in Fermi gases. Reviews
in Mathematical Physics. World Scientific. https://doi.org/10.1142/s0129055x20600090
chicago: Benedikter, Niels P. “Bosonic Collective Excitations in Fermi Gases.” Reviews
in Mathematical Physics. World Scientific, 2021. https://doi.org/10.1142/s0129055x20600090.
ieee: N. P. Benedikter, “Bosonic collective excitations in Fermi gases,” Reviews
in Mathematical Physics, vol. 33, no. 1. World Scientific, 2021.
ista: Benedikter NP. 2021. Bosonic collective excitations in Fermi gases. Reviews
in Mathematical Physics. 33(1), 2060009.
mla: Benedikter, Niels P. “Bosonic Collective Excitations in Fermi Gases.” Reviews
in Mathematical Physics, vol. 33, no. 1, 2060009, World Scientific, 2021,
doi:10.1142/s0129055x20600090.
short: N.P. Benedikter, Reviews in Mathematical Physics 33 (2021).
date_created: 2020-05-28T16:47:55Z
date_published: 2021-01-01T00:00:00Z
date_updated: 2023-09-05T16:07:40Z
day: '01'
department:
- _id: RoSe
doi: 10.1142/s0129055x20600090
ec_funded: 1
external_id:
arxiv:
- '1910.08190'
isi:
- '000613313200010'
intvolume: ' 33'
isi: 1
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1910.08190
month: '01'
oa: 1
oa_version: Preprint
project:
- _id: 25C6DC12-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '694227'
name: Analysis of quantum many-body systems
publication: Reviews in Mathematical Physics
publication_identifier:
eissn:
- 1793-6659
issn:
- 0129-055X
publication_status: published
publisher: World Scientific
quality_controlled: '1'
scopus_import: '1'
status: public
title: Bosonic collective excitations in Fermi gases
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 33
year: '2021'
...
---
_id: '7901'
abstract:
- lang: eng
text: We derive rigorously the leading order of the correlation energy of a Fermi
gas in a scaling regime of high density and weak interaction. The result verifies
the prediction of the random-phase approximation. Our proof refines the method
of collective bosonization in three dimensions. We approximately diagonalize an
effective Hamiltonian describing approximately bosonic collective excitations
around the Hartree–Fock state, while showing that gapless and non-collective excitations
have only a negligible effect on the ground state energy.
acknowledgement: We thank Christian Hainzl for helpful discussions and a referee for
very careful reading of the paper and many helpful suggestions. NB and RS were supported
by the European Research Council (ERC) under the European Union’s Horizon 2020 research
and innovation programme (grant agreement No. 694227). Part of the research of NB
was conducted on the RZD18 Nice–Milan–Vienna–Moscow. NB thanks Elliott H. Lieb and
Peter Otte for explanations about the Luttinger model. PTN has received funding
from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under
Germany’s Excellence Strategy (EXC-2111-390814868). MP acknowledges financial support
from the European Research Council (ERC) under the European Union’s Horizon 2020
research and innovation programme (ERC StG MaMBoQ, grant agreement No. 802901).
BS gratefully acknowledges financial support from the NCCR SwissMAP, from the Swiss
National Science Foundation through the Grant “Dynamical and energetic properties
of Bose-Einstein condensates” and from the European Research Council through the
ERC-AdG CLaQS (grant agreement No. 834782). All authors acknowledge support for
workshop participation from Mathematisches Forschungsinstitut Oberwolfach (Leibniz
Association). NB, PTN, BS, and RS acknowledge support for workshop participation
from Fondation des Treilles.
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Niels P
full_name: Benedikter, Niels P
id: 3DE6C32A-F248-11E8-B48F-1D18A9856A87
last_name: Benedikter
orcid: 0000-0002-1071-6091
- first_name: Phan Thành
full_name: Nam, Phan Thành
last_name: Nam
- first_name: Marcello
full_name: Porta, Marcello
last_name: Porta
- first_name: Benjamin
full_name: Schlein, Benjamin
last_name: Schlein
- first_name: Robert
full_name: Seiringer, Robert
id: 4AFD0470-F248-11E8-B48F-1D18A9856A87
last_name: Seiringer
orcid: 0000-0002-6781-0521
citation:
ama: Benedikter NP, Nam PT, Porta M, Schlein B, Seiringer R. Correlation energy
of a weakly interacting Fermi gas. Inventiones Mathematicae. 2021;225:885-979.
doi:10.1007/s00222-021-01041-5
apa: Benedikter, N. P., Nam, P. T., Porta, M., Schlein, B., & Seiringer, R.
(2021). Correlation energy of a weakly interacting Fermi gas. Inventiones Mathematicae.
Springer. https://doi.org/10.1007/s00222-021-01041-5
chicago: Benedikter, Niels P, Phan Thành Nam, Marcello Porta, Benjamin Schlein,
and Robert Seiringer. “Correlation Energy of a Weakly Interacting Fermi Gas.”
Inventiones Mathematicae. Springer, 2021. https://doi.org/10.1007/s00222-021-01041-5.
ieee: N. P. Benedikter, P. T. Nam, M. Porta, B. Schlein, and R. Seiringer, “Correlation
energy of a weakly interacting Fermi gas,” Inventiones Mathematicae, vol.
225. Springer, pp. 885–979, 2021.
ista: Benedikter NP, Nam PT, Porta M, Schlein B, Seiringer R. 2021. Correlation
energy of a weakly interacting Fermi gas. Inventiones Mathematicae. 225, 885–979.
mla: Benedikter, Niels P., et al. “Correlation Energy of a Weakly Interacting Fermi
Gas.” Inventiones Mathematicae, vol. 225, Springer, 2021, pp. 885–979,
doi:10.1007/s00222-021-01041-5.
short: N.P. Benedikter, P.T. Nam, M. Porta, B. Schlein, R. Seiringer, Inventiones
Mathematicae 225 (2021) 885–979.
date_created: 2020-05-28T16:48:20Z
date_published: 2021-05-03T00:00:00Z
date_updated: 2023-08-21T06:30:30Z
day: '03'
ddc:
- '510'
department:
- _id: RoSe
doi: 10.1007/s00222-021-01041-5
ec_funded: 1
external_id:
arxiv:
- '2005.08933'
isi:
- '000646573600001'
file:
- access_level: open_access
checksum: f38c79dfd828cdc7f49a34b37b83d376
content_type: application/pdf
creator: dernst
date_created: 2022-05-16T12:23:40Z
date_updated: 2022-05-16T12:23:40Z
file_id: '11386'
file_name: 2021_InventMath_Benedikter.pdf
file_size: 1089319
relation: main_file
success: 1
file_date_updated: 2022-05-16T12:23:40Z
has_accepted_license: '1'
intvolume: ' 225'
isi: 1
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
page: 885-979
project:
- _id: B67AFEDC-15C9-11EA-A837-991A96BB2854
name: IST Austria Open Access Fund
- _id: 25C6DC12-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '694227'
name: Analysis of quantum many-body systems
publication: Inventiones Mathematicae
publication_identifier:
eissn:
- 1432-1297
issn:
- 0020-9910
publication_status: published
publisher: Springer
quality_controlled: '1'
scopus_import: '1'
status: public
title: Correlation energy of a weakly interacting Fermi gas
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 225
year: '2021'
...
---
_id: '7905'
abstract:
- lang: eng
text: We investigate a sheaf-theoretic interpretation of stratification learning
from geometric and topological perspectives. Our main result is the construction
of stratification learning algorithms framed in terms of a sheaf on a partially
ordered set with the Alexandroff topology. We prove that the resulting decomposition
is the unique minimal stratification for which the strata are homogeneous and
the given sheaf is constructible. In particular, when we choose to work with the
local homology sheaf, our algorithm gives an alternative to the local homology
transfer algorithm given in Bendich et al. (Proceedings of the 23rd Annual ACM-SIAM
Symposium on Discrete Algorithms, pp. 1355–1370, ACM, New York, 2012), and the
cohomology stratification algorithm given in Nanda (Found. Comput. Math. 20(2),
195–222, 2020). Additionally, we give examples of stratifications based on the
geometric techniques of Breiding et al. (Rev. Mat. Complut. 31(3), 545–593, 2018),
illustrating how the sheaf-theoretic approach can be used to study stratifications
from both topological and geometric perspectives. This approach also points toward
future applications of sheaf theory in the study of topological data analysis
by illustrating the utility of the language of sheaf theory in generalizing existing
algorithms.
acknowledgement: Open access funding provided by Institute of Science and Technology
(IST Austria). This work was partially supported by NSF IIS-1513616 and NSF ABI-1661375.
The authors would like to thank the anonymous referees for their insightful comments.
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Adam
full_name: Brown, Adam
id: 70B7FDF6-608D-11E9-9333-8535E6697425
last_name: Brown
- first_name: Bei
full_name: Wang, Bei
last_name: Wang
citation:
ama: Brown A, Wang B. Sheaf-theoretic stratification learning from geometric and
topological perspectives. Discrete and Computational Geometry. 2021;65:1166-1198.
doi:10.1007/s00454-020-00206-y
apa: Brown, A., & Wang, B. (2021). Sheaf-theoretic stratification learning from
geometric and topological perspectives. Discrete and Computational Geometry.
Springer Nature. https://doi.org/10.1007/s00454-020-00206-y
chicago: Brown, Adam, and Bei Wang. “Sheaf-Theoretic Stratification Learning from
Geometric and Topological Perspectives.” Discrete and Computational Geometry.
Springer Nature, 2021. https://doi.org/10.1007/s00454-020-00206-y.
ieee: A. Brown and B. Wang, “Sheaf-theoretic stratification learning from geometric
and topological perspectives,” Discrete and Computational Geometry, vol.
65. Springer Nature, pp. 1166–1198, 2021.
ista: Brown A, Wang B. 2021. Sheaf-theoretic stratification learning from geometric
and topological perspectives. Discrete and Computational Geometry. 65, 1166–1198.
mla: Brown, Adam, and Bei Wang. “Sheaf-Theoretic Stratification Learning from Geometric
and Topological Perspectives.” Discrete and Computational Geometry, vol.
65, Springer Nature, 2021, pp. 1166–98, doi:10.1007/s00454-020-00206-y.
short: A. Brown, B. Wang, Discrete and Computational Geometry 65 (2021) 1166–1198.
date_created: 2020-05-30T10:26:04Z
date_published: 2021-06-01T00:00:00Z
date_updated: 2024-03-07T15:01:58Z
day: '01'
ddc:
- '510'
department:
- _id: HeEd
doi: 10.1007/s00454-020-00206-y
external_id:
arxiv:
- '1712.07734'
isi:
- '000536324700001'
file:
- access_level: open_access
checksum: 487a84ea5841b75f04f66d7ebd71b67e
content_type: application/pdf
creator: dernst
date_created: 2020-11-25T09:06:41Z
date_updated: 2020-11-25T09:06:41Z
file_id: '8803'
file_name: 2020_DiscreteCompGeometry_Brown.pdf
file_size: 1013730
relation: main_file
success: 1
file_date_updated: 2020-11-25T09:06:41Z
has_accepted_license: '1'
intvolume: ' 65'
isi: 1
language:
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month: '06'
oa: 1
oa_version: Published Version
page: 1166-1198
project:
- _id: B67AFEDC-15C9-11EA-A837-991A96BB2854
name: IST Austria Open Access Fund
publication: Discrete and Computational Geometry
publication_identifier:
eissn:
- 1432-0444
issn:
- 0179-5376
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Sheaf-theoretic stratification learning from geometric and topological perspectives
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 65
year: '2021'
...
---
_id: '7925'
abstract:
- lang: eng
text: In this paper, we introduce a relaxed CQ method with alternated inertial step
for solving split feasibility problems. We give convergence of the sequence generated
by our method under some suitable assumptions. Some numerical implementations
from sparse signal and image deblurring are reported to show the efficiency of
our method.
acknowledgement: Open access funding provided by Institute of Science and Technology
(IST Austria). The authors are grateful to the referees for their insightful comments
which have improved the earlier version of the manuscript greatly. The first author
has received funding from the European Research Council (ERC) under the European
Union’s Seventh Framework Program (FP7-2007-2013) (Grant agreement No. 616160).
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Yekini
full_name: Shehu, Yekini
id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87
last_name: Shehu
orcid: 0000-0001-9224-7139
- first_name: Aviv
full_name: Gibali, Aviv
last_name: Gibali
citation:
ama: Shehu Y, Gibali A. New inertial relaxed method for solving split feasibilities.
Optimization Letters. 2021;15:2109-2126. doi:10.1007/s11590-020-01603-1
apa: Shehu, Y., & Gibali, A. (2021). New inertial relaxed method for solving
split feasibilities. Optimization Letters. Springer Nature. https://doi.org/10.1007/s11590-020-01603-1
chicago: Shehu, Yekini, and Aviv Gibali. “New Inertial Relaxed Method for Solving
Split Feasibilities.” Optimization Letters. Springer Nature, 2021. https://doi.org/10.1007/s11590-020-01603-1.
ieee: Y. Shehu and A. Gibali, “New inertial relaxed method for solving split feasibilities,”
Optimization Letters, vol. 15. Springer Nature, pp. 2109–2126, 2021.
ista: Shehu Y, Gibali A. 2021. New inertial relaxed method for solving split feasibilities.
Optimization Letters. 15, 2109–2126.
mla: Shehu, Yekini, and Aviv Gibali. “New Inertial Relaxed Method for Solving Split
Feasibilities.” Optimization Letters, vol. 15, Springer Nature, 2021, pp.
2109–26, doi:10.1007/s11590-020-01603-1.
short: Y. Shehu, A. Gibali, Optimization Letters 15 (2021) 2109–2126.
date_created: 2020-06-04T11:28:33Z
date_published: 2021-09-01T00:00:00Z
date_updated: 2024-03-07T15:00:43Z
day: '01'
ddc:
- '510'
department:
- _id: VlKo
doi: 10.1007/s11590-020-01603-1
ec_funded: 1
external_id:
isi:
- '000537342300001'
file:
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checksum: 63c5f31cd04626152a19f97a2476281b
content_type: application/pdf
creator: kschuh
date_created: 2024-03-07T14:58:51Z
date_updated: 2024-03-07T14:58:51Z
file_id: '15089'
file_name: 2021_OptimizationLetters_Shehu.pdf
file_size: 2148882
relation: main_file
success: 1
file_date_updated: 2024-03-07T14:58:51Z
has_accepted_license: '1'
intvolume: ' 15'
isi: 1
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 2109-2126
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
- _id: B67AFEDC-15C9-11EA-A837-991A96BB2854
name: IST Austria Open Access Fund
publication: Optimization Letters
publication_identifier:
eissn:
- 1862-4480
issn:
- 1862-4472
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: New inertial relaxed method for solving split feasibilities
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 15
year: '2021'
...
---
_id: '7939'
abstract:
- lang: eng
text: "We design fast deterministic algorithms for distance computation in the Congested
Clique model. Our key contributions include:\r\n A (2+ϵ)-approximation for
all-pairs shortest paths in O(log2n/ϵ) rounds on unweighted undirected graphs.
With a small additional additive factor, this also applies for weighted graphs.
This is the first sub-polynomial constant-factor approximation for APSP in this
model.\r\n A (1+ϵ)-approximation for multi-source shortest paths from O(n−−√)
sources in O(log2n/ϵ) rounds on weighted undirected graphs. This is the first
sub-polynomial algorithm obtaining this approximation for a set of sources of
polynomial size.\r\n\r\nOur main techniques are new distance tools that are obtained
via improved algorithms for sparse matrix multiplication, which we leverage to
construct efficient hopsets and shortest paths. Furthermore, our techniques extend
to additional distance problems for which we improve upon the state-of-the-art,
including diameter approximation, and an exact single-source shortest paths algorithm
for weighted undirected graphs in O~(n1/6) rounds. "
acknowledgement: Open access funding provided by Institute of Science and Technology
(IST Austria). We thank Mohsen Ghaffari, Michael Elkin and Merav Parter for fruitful
discussions. This project has received funding from the European Union’s Horizon
2020 Research And Innovation Program under Grant Agreement No. 755839.
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Keren
full_name: Censor-Hillel, Keren
last_name: Censor-Hillel
- first_name: Michal
full_name: Dory, Michal
last_name: Dory
- first_name: Janne
full_name: Korhonen, Janne
id: C5402D42-15BC-11E9-A202-CA2BE6697425
last_name: Korhonen
- first_name: Dean
full_name: Leitersdorf, Dean
last_name: Leitersdorf
citation:
ama: Censor-Hillel K, Dory M, Korhonen J, Leitersdorf D. Fast approximate shortest
paths in the congested clique. Distributed Computing. 2021;34:463-487.
doi:10.1007/s00446-020-00380-5
apa: Censor-Hillel, K., Dory, M., Korhonen, J., & Leitersdorf, D. (2021). Fast
approximate shortest paths in the congested clique. Distributed Computing.
Springer Nature. https://doi.org/10.1007/s00446-020-00380-5
chicago: Censor-Hillel, Keren, Michal Dory, Janne Korhonen, and Dean Leitersdorf.
“Fast Approximate Shortest Paths in the Congested Clique.” Distributed Computing.
Springer Nature, 2021. https://doi.org/10.1007/s00446-020-00380-5.
ieee: K. Censor-Hillel, M. Dory, J. Korhonen, and D. Leitersdorf, “Fast approximate
shortest paths in the congested clique,” Distributed Computing, vol. 34.
Springer Nature, pp. 463–487, 2021.
ista: Censor-Hillel K, Dory M, Korhonen J, Leitersdorf D. 2021. Fast approximate
shortest paths in the congested clique. Distributed Computing. 34, 463–487.
mla: Censor-Hillel, Keren, et al. “Fast Approximate Shortest Paths in the Congested
Clique.” Distributed Computing, vol. 34, Springer Nature, 2021, pp. 463–87,
doi:10.1007/s00446-020-00380-5.
short: K. Censor-Hillel, M. Dory, J. Korhonen, D. Leitersdorf, Distributed Computing
34 (2021) 463–487.
date_created: 2020-06-07T22:00:54Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2024-03-07T14:43:39Z
day: '01'
department:
- _id: DaAl
doi: 10.1007/s00446-020-00380-5
external_id:
arxiv:
- '1903.05956'
isi:
- '000556444600001'
intvolume: ' 34'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1007/s00446-020-00380-5
month: '12'
oa: 1
oa_version: Published Version
page: 463-487
project:
- _id: B67AFEDC-15C9-11EA-A837-991A96BB2854
name: IST Austria Open Access Fund
publication: Distributed Computing
publication_identifier:
eissn:
- 1432-0452
issn:
- 0178-2770
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '6933'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Fast approximate shortest paths in the congested clique
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
_id: '7941'
abstract:
- lang: eng
text: Expansion microscopy is a recently developed super-resolution imaging technique,
which provides an alternative to optics-based methods such as deterministic approaches
(e.g. STED) or stochastic approaches (e.g. PALM/STORM). The idea behind expansion
microscopy is to embed the biological sample in a swellable gel, and then to expand
it isotropically, thereby increasing the distance between the fluorophores. This
approach breaks the diffraction barrier by simply separating the emission point-spread-functions
of the fluorophores. The resolution attainable in expansion microscopy is thus
directly dependent on the separation that can be achieved, i.e. on the expansion
factor. The original implementation of the technique achieved an expansion factor
of fourfold, for a resolution of 70–80 nm. The subsequently developed X10 method
achieves an expansion factor of 10-fold, for a resolution of 25–30 nm. This technique
can be implemented with minimal technical requirements on any standard fluorescence
microscope, and is more easily applied for multi-color imaging than either deterministic
or stochastic super-resolution approaches. This renders X10 expansion microscopy
a highly promising tool for new biological discoveries, as discussed here, and
as demonstrated by several recent applications.
article_processing_charge: No
author:
- first_name: Sven M
full_name: Truckenbrodt, Sven M
id: 45812BD4-F248-11E8-B48F-1D18A9856A87
last_name: Truckenbrodt
- first_name: Silvio O.
full_name: Rizzoli, Silvio O.
last_name: Rizzoli
citation:
ama: 'Truckenbrodt SM, Rizzoli SO. Simple multi-color super-resolution by X10 microscopy.
In: Methods in Cell Biology. Vol 161. Elsevier; 2021:33-56. doi:10.1016/bs.mcb.2020.04.016'
apa: Truckenbrodt, S. M., & Rizzoli, S. O. (2021). Simple multi-color super-resolution
by X10 microscopy. In Methods in Cell Biology (Vol. 161, pp. 33–56). Elsevier.
https://doi.org/10.1016/bs.mcb.2020.04.016
chicago: Truckenbrodt, Sven M, and Silvio O. Rizzoli. “Simple Multi-Color Super-Resolution
by X10 Microscopy.” In Methods in Cell Biology, 161:33–56. Elsevier, 2021.
https://doi.org/10.1016/bs.mcb.2020.04.016.
ieee: S. M. Truckenbrodt and S. O. Rizzoli, “Simple multi-color super-resolution
by X10 microscopy,” in Methods in Cell Biology, vol. 161, Elsevier, 2021,
pp. 33–56.
ista: 'Truckenbrodt SM, Rizzoli SO. 2021.Simple multi-color super-resolution by
X10 microscopy. In: Methods in Cell Biology. vol. 161, 33–56.'
mla: Truckenbrodt, Sven M., and Silvio O. Rizzoli. “Simple Multi-Color Super-Resolution
by X10 Microscopy.” Methods in Cell Biology, vol. 161, Elsevier, 2021,
pp. 33–56, doi:10.1016/bs.mcb.2020.04.016.
short: S.M. Truckenbrodt, S.O. Rizzoli, in:, Methods in Cell Biology, Elsevier,
2021, pp. 33–56.
date_created: 2020-06-07T22:00:55Z
date_published: 2021-01-01T00:00:00Z
date_updated: 2021-03-11T08:49:08Z
day: '01'
department:
- _id: JoDa
doi: 10.1016/bs.mcb.2020.04.016
external_id:
pmid:
- '33478696'
intvolume: ' 161'
language:
- iso: eng
month: '01'
oa_version: None
page: 33-56
pmid: 1
publication: Methods in Cell Biology
publication_identifier:
isbn:
- 978012820807-6
issn:
- 0091-679X
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Simple multi-color super-resolution by X10 microscopy
type: book_chapter
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 161
year: '2021'
...
---
_id: '8196'
abstract:
- lang: eng
text: This paper aims to obtain a strong convergence result for a Douglas–Rachford
splitting method with inertial extrapolation step for finding a zero of the sum
of two set-valued maximal monotone operators without any further assumption of
uniform monotonicity on any of the involved maximal monotone operators. Furthermore,
our proposed method is easy to implement and the inertial factor in our proposed
method is a natural choice. Our method of proof is of independent interest. Finally,
some numerical implementations are given to confirm the theoretical analysis.
acknowledgement: Open access funding provided by Institute of Science and Technology
(IST Austria). The project of Yekini Shehu has received funding from the European
Research Council (ERC) under the European Union’s Seventh Framework Program (FP7—2007–2013)
(Grant Agreement No. 616160). The authors are grateful to the anonymous referees
and the handling Editor for their comments and suggestions which have improved the
earlier version of the manuscript greatly.
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Yekini
full_name: Shehu, Yekini
id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87
last_name: Shehu
orcid: 0000-0001-9224-7139
- first_name: Qiao-Li
full_name: Dong, Qiao-Li
last_name: Dong
- first_name: Lu-Lu
full_name: Liu, Lu-Lu
last_name: Liu
- first_name: Jen-Chih
full_name: Yao, Jen-Chih
last_name: Yao
citation:
ama: Shehu Y, Dong Q-L, Liu L-L, Yao J-C. New strong convergence method for the
sum of two maximal monotone operators. Optimization and Engineering. 2021;22:2627-2653.
doi:10.1007/s11081-020-09544-5
apa: Shehu, Y., Dong, Q.-L., Liu, L.-L., & Yao, J.-C. (2021). New strong convergence
method for the sum of two maximal monotone operators. Optimization and Engineering.
Springer Nature. https://doi.org/10.1007/s11081-020-09544-5
chicago: Shehu, Yekini, Qiao-Li Dong, Lu-Lu Liu, and Jen-Chih Yao. “New Strong Convergence
Method for the Sum of Two Maximal Monotone Operators.” Optimization and Engineering.
Springer Nature, 2021. https://doi.org/10.1007/s11081-020-09544-5.
ieee: Y. Shehu, Q.-L. Dong, L.-L. Liu, and J.-C. Yao, “New strong convergence method
for the sum of two maximal monotone operators,” Optimization and Engineering,
vol. 22. Springer Nature, pp. 2627–2653, 2021.
ista: Shehu Y, Dong Q-L, Liu L-L, Yao J-C. 2021. New strong convergence method for
the sum of two maximal monotone operators. Optimization and Engineering. 22, 2627–2653.
mla: Shehu, Yekini, et al. “New Strong Convergence Method for the Sum of Two Maximal
Monotone Operators.” Optimization and Engineering, vol. 22, Springer Nature,
2021, pp. 2627–53, doi:10.1007/s11081-020-09544-5.
short: Y. Shehu, Q.-L. Dong, L.-L. Liu, J.-C. Yao, Optimization and Engineering
22 (2021) 2627–2653.
date_created: 2020-08-03T14:29:57Z
date_published: 2021-02-25T00:00:00Z
date_updated: 2024-03-07T14:39:29Z
day: '25'
ddc:
- '510'
department:
- _id: VlKo
doi: 10.1007/s11081-020-09544-5
ec_funded: 1
external_id:
isi:
- '000559345400001'
file:
- access_level: open_access
content_type: application/pdf
creator: dernst
date_created: 2020-08-03T15:24:39Z
date_updated: 2020-08-03T15:24:39Z
file_id: '8197'
file_name: 2020_OptimizationEngineering_Shehu.pdf
file_size: 2137860
relation: main_file
success: 1
file_date_updated: 2020-08-03T15:24:39Z
has_accepted_license: '1'
intvolume: ' 22'
isi: 1
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: 2627-2653
project:
- _id: B67AFEDC-15C9-11EA-A837-991A96BB2854
name: IST Austria Open Access Fund
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: Optimization and Engineering
publication_identifier:
eissn:
- 1573-2924
issn:
- 1389-4420
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: New strong convergence method for the sum of two maximal monotone operators
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 22
year: '2021'
...
---
_id: '8198'
abstract:
- lang: eng
text: We investigate how the critical driving amplitude at the Floquet many-body
localized (MBL) to ergodic phase transition differs between smooth and nonsmooth
drives. To this end, we numerically study a disordered spin-1/2 chain which is
periodically driven by a sine or square-wave drive over a wide range of driving
frequencies. In both cases the critical driving amplitude increases monotonically
with the frequency, and at large frequencies it is identical for the two drives.
However, at low and intermediate frequencies the critical amplitude of the square-wave
drive depends strongly on the frequency, while that of the sinusoidal drive is
almost constant over a wide frequency range. By analyzing the density of drive-induced
resonances we conclude that this difference is due to resonances induced by the
higher harmonics which are present (absent) in the Fourier spectrum of the square-wave
(sine) drive. Furthermore, we suggest a numerically efficient method for estimating
the frequency dependence of the critical driving amplitudes for different drives
which is based on calculating the density of drive-induced resonances. We conclude
that delocalization occurs once the density of drive-induced resonances reaches
a critical value determined only by the static system.
acknowledgement: We thank Y. Bar Lev, T. Biadse, and, particularly, E. Bairey and
B. Katzir for illuminating discussions and their many insights and help. The authors
thank N. Lindner for his support throughout this project. We are further grateful
to M. Serbyn, A. Kamenev, A. Turner, and S. de Nicola for reading the manuscript
and providing good feedback and suggestions. We acknowledge financial support from
the Defense Advanced Research Projects Agency through the DRINQS program, Grant
No. D18AC00025. T.G. was in part supported by an Aly Kaufman Fellowship at the Technion.
T.G. acknowledges funding from the Institute of Science and Technology (IST) Austria
and from the European Union’s Horizon 2020 research and innovation program under
Marie SkłodowskaCurie Grant Agreement No. 754411.under the Marie Skłodowska-Curie
Grant Agreement No.754411.
article_number: '214204'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Asaf A.
full_name: Diringer, Asaf A.
last_name: Diringer
- first_name: Tobias
full_name: Gulden, Tobias
id: 1083E038-9F73-11E9-A4B5-532AE6697425
last_name: Gulden
orcid: 0000-0001-6814-7541
citation:
ama: Diringer AA, Gulden T. Impact of drive harmonics on the stability of Floquet
many-body localization. Physical Review B. 2021;103(21). doi:10.1103/PhysRevB.103.214204
apa: Diringer, A. A., & Gulden, T. (2021). Impact of drive harmonics on the
stability of Floquet many-body localization. Physical Review B. American
Physical Society. https://doi.org/10.1103/PhysRevB.103.214204
chicago: Diringer, Asaf A., and Tobias Gulden. “Impact of Drive Harmonics on the
Stability of Floquet Many-Body Localization.” Physical Review B. American
Physical Society, 2021. https://doi.org/10.1103/PhysRevB.103.214204.
ieee: A. A. Diringer and T. Gulden, “Impact of drive harmonics on the stability
of Floquet many-body localization,” Physical Review B, vol. 103, no. 21.
American Physical Society, 2021.
ista: Diringer AA, Gulden T. 2021. Impact of drive harmonics on the stability of
Floquet many-body localization. Physical Review B. 103(21), 214204.
mla: Diringer, Asaf A., and Tobias Gulden. “Impact of Drive Harmonics on the Stability
of Floquet Many-Body Localization.” Physical Review B, vol. 103, no. 21,
214204, American Physical Society, 2021, doi:10.1103/PhysRevB.103.214204.
short: A.A. Diringer, T. Gulden, Physical Review B 103 (2021).
date_created: 2020-08-04T13:03:40Z
date_published: 2021-06-21T00:00:00Z
date_updated: 2023-08-04T10:56:33Z
day: '21'
department:
- _id: MaSe
doi: 10.1103/PhysRevB.103.214204
ec_funded: 1
external_id:
arxiv:
- '2007.14879'
isi:
- '000664429700005'
intvolume: ' 103'
isi: 1
issue: '21'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2007.14879
month: '06'
oa: 1
oa_version: Preprint
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Physical Review B
publication_identifier:
eissn:
- '24699969'
issn:
- '24699950'
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
status: public
title: Impact of drive harmonics on the stability of Floquet many-body localization
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 103
year: '2021'
...
---
_id: '8248'
abstract:
- lang: eng
text: 'We consider the following setting: suppose that we are given a manifold M
in Rd with positive reach. Moreover assume that we have an embedded simplical
complex A without boundary, whose vertex set lies on the manifold, is sufficiently
dense and such that all simplices in A have sufficient quality. We prove that
if, locally, interiors of the projection of the simplices onto the tangent space
do not intersect, then A is a triangulation of the manifold, that is, they are
homeomorphic.'
acknowledgement: "Open access funding provided by the Institute of Science and Technology
(IST Austria). Arijit Ghosh is supported by the Ramanujan Fellowship (No. SB/S2/RJN-064/2015),
India.\r\nThis work has been funded by the European Research Council under the European
Union’s ERC Grant Agreement number 339025 GUDHI (Algorithmic Foundations of Geometric
Understanding in Higher Dimensions). The third author is supported by Ramanujan
Fellowship (No. SB/S2/RJN-064/2015), India. The fifth author also received funding
from the European Union’s Horizon 2020 research and innovation programme under the
Marie Skłodowska-Curie Grant Agreement No. 754411."
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Jean-Daniel
full_name: Boissonnat, Jean-Daniel
last_name: Boissonnat
- first_name: Ramsay
full_name: Dyer, Ramsay
last_name: Dyer
- first_name: Arijit
full_name: Ghosh, Arijit
last_name: Ghosh
- first_name: Andre
full_name: Lieutier, Andre
last_name: Lieutier
- first_name: Mathijs
full_name: Wintraecken, Mathijs
id: 307CFBC8-F248-11E8-B48F-1D18A9856A87
last_name: Wintraecken
orcid: 0000-0002-7472-2220
citation:
ama: Boissonnat J-D, Dyer R, Ghosh A, Lieutier A, Wintraecken M. Local conditions
for triangulating submanifolds of Euclidean space. Discrete and Computational
Geometry. 2021;66:666-686. doi:10.1007/s00454-020-00233-9
apa: Boissonnat, J.-D., Dyer, R., Ghosh, A., Lieutier, A., & Wintraecken, M.
(2021). Local conditions for triangulating submanifolds of Euclidean space. Discrete
and Computational Geometry. Springer Nature. https://doi.org/10.1007/s00454-020-00233-9
chicago: Boissonnat, Jean-Daniel, Ramsay Dyer, Arijit Ghosh, Andre Lieutier, and
Mathijs Wintraecken. “Local Conditions for Triangulating Submanifolds of Euclidean
Space.” Discrete and Computational Geometry. Springer Nature, 2021. https://doi.org/10.1007/s00454-020-00233-9.
ieee: J.-D. Boissonnat, R. Dyer, A. Ghosh, A. Lieutier, and M. Wintraecken, “Local
conditions for triangulating submanifolds of Euclidean space,” Discrete and
Computational Geometry, vol. 66. Springer Nature, pp. 666–686, 2021.
ista: Boissonnat J-D, Dyer R, Ghosh A, Lieutier A, Wintraecken M. 2021. Local conditions
for triangulating submanifolds of Euclidean space. Discrete and Computational
Geometry. 66, 666–686.
mla: Boissonnat, Jean-Daniel, et al. “Local Conditions for Triangulating Submanifolds
of Euclidean Space.” Discrete and Computational Geometry, vol. 66, Springer
Nature, 2021, pp. 666–86, doi:10.1007/s00454-020-00233-9.
short: J.-D. Boissonnat, R. Dyer, A. Ghosh, A. Lieutier, M. Wintraecken, Discrete
and Computational Geometry 66 (2021) 666–686.
date_created: 2020-08-11T07:11:51Z
date_published: 2021-09-01T00:00:00Z
date_updated: 2024-03-07T14:54:59Z
day: '01'
ddc:
- '510'
department:
- _id: HeEd
doi: 10.1007/s00454-020-00233-9
ec_funded: 1
external_id:
isi:
- '000558119300001'
has_accepted_license: '1'
intvolume: ' 66'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1007/s00454-020-00233-9
month: '09'
oa: 1
oa_version: Published Version
page: 666-686
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Discrete and Computational Geometry
publication_identifier:
eissn:
- 1432-0444
issn:
- 0179-5376
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Local conditions for triangulating submanifolds of Euclidean space
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 66
year: '2021'
...
---
_id: '8253'
abstract:
- lang: eng
text: Brains process information in spiking neural networks. Their intricate connections
shape the diverse functions these networks perform. In comparison, the functional
capabilities of models of spiking networks are still rudimentary. This shortcoming
is mainly due to the lack of insight and practical algorithms to construct the
necessary connectivity. Any such algorithm typically attempts to build networks
by iteratively reducing the error compared to a desired output. But assigning
credit to hidden units in multi-layered spiking networks has remained challenging
due to the non-differentiable nonlinearity of spikes. To avoid this issue, one
can employ surrogate gradients to discover the required connectivity in spiking
network models. However, the choice of a surrogate is not unique, raising the
question of how its implementation influences the effectiveness of the method.
Here, we use numerical simulations to systematically study how essential design
parameters of surrogate gradients impact learning performance on a range of classification
problems. We show that surrogate gradient learning is robust to different shapes
of underlying surrogate derivatives, but the choice of the derivative’s scale
can substantially affect learning performance. When we combine surrogate gradients
with a suitable activity regularization technique, robust information processing
can be achieved in spiking networks even at the sparse activity limit. Our study
provides a systematic account of the remarkable robustness of surrogate gradient
learning and serves as a practical guide to model functional spiking neural networks.
acknowledgement: F.Z. was supported by the Wellcome Trust (110124/Z/15/Z) and the
Novartis Research Foundation. T.P.V. was supported by a Wellcome Trust Sir Henry
Dale Research fellowship (WT100000), a Wellcome Trust Senior Research Fellowship
(214316/Z/18/Z), and an ERC Consolidator Grant SYNAPSEEK.
article_processing_charge: No
article_type: original
author:
- first_name: Friedemann
full_name: Zenke, Friedemann
last_name: Zenke
orcid: 0000-0003-1883-644X
- first_name: Tim P
full_name: Vogels, Tim P
id: CB6FF8D2-008F-11EA-8E08-2637E6697425
last_name: Vogels
orcid: 0000-0003-3295-6181
citation:
ama: Zenke F, Vogels TP. The remarkable robustness of surrogate gradient learning
for instilling complex function in spiking neural networks. Neural Computation.
2021;33(4):899-925. doi:10.1162/neco_a_01367
apa: Zenke, F., & Vogels, T. P. (2021). The remarkable robustness of surrogate
gradient learning for instilling complex function in spiking neural networks.
Neural Computation. MIT Press. https://doi.org/10.1162/neco_a_01367
chicago: Zenke, Friedemann, and Tim P Vogels. “The Remarkable Robustness of Surrogate
Gradient Learning for Instilling Complex Function in Spiking Neural Networks.”
Neural Computation. MIT Press, 2021. https://doi.org/10.1162/neco_a_01367.
ieee: F. Zenke and T. P. Vogels, “The remarkable robustness of surrogate gradient
learning for instilling complex function in spiking neural networks,” Neural
Computation, vol. 33, no. 4. MIT Press, pp. 899–925, 2021.
ista: Zenke F, Vogels TP. 2021. The remarkable robustness of surrogate gradient
learning for instilling complex function in spiking neural networks. Neural Computation.
33(4), 899–925.
mla: Zenke, Friedemann, and Tim P. Vogels. “The Remarkable Robustness of Surrogate
Gradient Learning for Instilling Complex Function in Spiking Neural Networks.”
Neural Computation, vol. 33, no. 4, MIT Press, 2021, pp. 899–925, doi:10.1162/neco_a_01367.
short: F. Zenke, T.P. Vogels, Neural Computation 33 (2021) 899–925.
date_created: 2020-08-12T12:08:24Z
date_published: 2021-03-01T00:00:00Z
date_updated: 2023-08-04T10:53:14Z
day: '01'
ddc:
- '000'
- '570'
department:
- _id: TiVo
doi: 10.1162/neco_a_01367
ec_funded: 1
external_id:
isi:
- '000663433900003'
pmid:
- '33513328'
file:
- access_level: open_access
checksum: eac5a51c24c8989ae7cf9ae32ec3bc95
content_type: application/pdf
creator: dernst
date_created: 2022-04-08T06:05:39Z
date_updated: 2022-04-08T06:05:39Z
file_id: '11131'
file_name: 2021_NeuralComputation_Zenke.pdf
file_size: 1611614
relation: main_file
success: 1
file_date_updated: 2022-04-08T06:05:39Z
has_accepted_license: '1'
intvolume: ' 33'
isi: 1
issue: '4'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: 899-925
pmid: 1
project:
- _id: 0aacfa84-070f-11eb-9043-d7eb2c709234
call_identifier: H2020
grant_number: '819603'
name: Learning the shape of synaptic plasticity rules for neuronal architectures
and function through machine learning.
- _id: c084a126-5a5b-11eb-8a69-d75314a70a87
grant_number: 214316/Z/18/Z
name: What’s in a memory? Spatiotemporal dynamics in strongly coupled recurrent
neuronal networks.
publication: Neural Computation
publication_identifier:
eissn:
- 1530-888X
issn:
- 0899-7667
publication_status: published
publisher: MIT Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: The remarkable robustness of surrogate gradient learning for instilling complex
function in spiking neural networks
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 33
year: '2021'
...
---
_id: '8286'
abstract:
- lang: eng
text: "We consider the following dynamic load-balancing process: given an underlying
graph G with n nodes, in each step t≥ 0, one unit of load is created, and placed
at a randomly chosen graph node. In the same step, the chosen node picks a random
neighbor, and the two nodes balance their loads by averaging them. We are interested
in the expected gap between the minimum and maximum loads at nodes as the process
progresses, and its dependence on n and on the graph structure. Variants of the
above graphical balanced allocation process have been studied previously by Peres,
Talwar, and Wieder [Peres et al., 2015], and by Sauerwald and Sun [Sauerwald and
Sun, 2015]. These authors left as open the question of characterizing the gap
in the case of cycle graphs in the dynamic case, where weights are created during
the algorithm’s execution. For this case, the only known upper bound is of \U0001D4AA(n
log n), following from a majorization argument due to [Peres et al., 2015], which
analyzes a related graphical allocation process. In this paper, we provide an
upper bound of \U0001D4AA (√n log n) on the expected gap of the above process
for cycles of length n. We introduce a new potential analysis technique, which
enables us to bound the difference in load between k-hop neighbors on the cycle,
for any k ≤ n/2. We complement this with a \"gap covering\" argument, which bounds
the maximum value of the gap by bounding its value across all possible subsets
of a certain structure, and recursively bounding the gaps within each subset.
We provide analytical and experimental evidence that our upper bound on the gap
is tight up to a logarithmic factor. "
acknowledgement: The authors sincerely thank Thomas Sauerwald and George Giakkoupis
for insightful discussions, and Mohsen Ghaffari, Yuval Peres, and Udi Wieder for
feedback on earlier versions of this draft. We also thank the ICALP anonymous reviewers
for their very useful comments. Open access funding provided by Institute of Science
and Technology (IST Austria). Funding was provided by European Research Council
(Grant No. PR1042ERC01).
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
- first_name: Giorgi
full_name: Nadiradze, Giorgi
id: 3279A00C-F248-11E8-B48F-1D18A9856A87
last_name: Nadiradze
orcid: 0000-0001-5634-0731
- first_name: Amirmojtaba
full_name: Sabour, Amirmojtaba
id: bcc145fd-e77f-11ea-ae8b-80d661dbff67
last_name: Sabour
citation:
ama: Alistarh D-A, Nadiradze G, Sabour A. Dynamic averaging load balancing on cycles.
Algorithmica. 2021. doi:10.1007/s00453-021-00905-9
apa: 'Alistarh, D.-A., Nadiradze, G., & Sabour, A. (2021). Dynamic averaging
load balancing on cycles. Algorithmica. Virtual, Online; Germany: Springer
Nature. https://doi.org/10.1007/s00453-021-00905-9'
chicago: Alistarh, Dan-Adrian, Giorgi Nadiradze, and Amirmojtaba Sabour. “Dynamic
Averaging Load Balancing on Cycles.” Algorithmica. Springer Nature, 2021.
https://doi.org/10.1007/s00453-021-00905-9.
ieee: D.-A. Alistarh, G. Nadiradze, and A. Sabour, “Dynamic averaging load balancing
on cycles,” Algorithmica. Springer Nature, 2021.
ista: Alistarh D-A, Nadiradze G, Sabour A. 2021. Dynamic averaging load balancing
on cycles. Algorithmica.
mla: Alistarh, Dan-Adrian, et al. “Dynamic Averaging Load Balancing on Cycles.”
Algorithmica, Springer Nature, 2021, doi:10.1007/s00453-021-00905-9.
short: D.-A. Alistarh, G. Nadiradze, A. Sabour, Algorithmica (2021).
conference:
end_date: 2020-07-11
location: Virtual, Online; Germany
name: 'ICALP: International Colloquium on Automata, Languages, and Programming '
start_date: 2020-07-08
date_created: 2020-08-24T06:24:04Z
date_published: 2021-12-24T00:00:00Z
date_updated: 2024-03-05T07:35:53Z
day: '24'
ddc:
- '000'
department:
- _id: DaAl
doi: 10.1007/s00453-021-00905-9
ec_funded: 1
external_id:
arxiv:
- '2003.09297'
isi:
- '000734004600001'
file:
- access_level: open_access
checksum: 21169b25b0c8e17b21e12af22bff9870
content_type: application/pdf
creator: cchlebak
date_created: 2021-12-27T10:36:40Z
date_updated: 2021-12-27T10:36:40Z
file_id: '10577'
file_name: 2021_Algorithmica_Alistarh.pdf
file_size: 525950
relation: main_file
success: 1
file_date_updated: 2021-12-27T10:36:40Z
has_accepted_license: '1'
isi: 1
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
- _id: B67AFEDC-15C9-11EA-A837-991A96BB2854
name: IST Austria Open Access Fund
publication: Algorithmica
publication_identifier:
eissn:
- 1432-0541
issn:
- 0178-4617
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
link:
- relation: earlier_version
url: https://doi.org/10.4230/LIPIcs.ICALP.2020.7
record:
- id: '15077'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Dynamic averaging load balancing on cycles
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
year: '2021'
...
---
_id: '8317'
abstract:
- lang: eng
text: When can a polyomino piece of paper be folded into a unit cube? Prior work
studied tree-like polyominoes, but polyominoes with holes remain an intriguing
open problem. We present sufficient conditions for a polyomino with one or several
holes to fold into a cube, and conditions under which cube folding is impossible.
In particular, we show that all but five special “basic” holes guarantee foldability.
acknowledgement: This research was performed in part at the 33rd Bellairs Winter Workshop
on Computational Geometry. We thank all other participants for a fruitful atmosphere.
H. Akitaya was supported by NSF CCF-1422311 & 1423615. Z. Masárová was partially
funded by Wittgenstein Prize, Austrian Science Fund (FWF), grant no. Z 342-N31.
article_number: '101700'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Oswin
full_name: Aichholzer, Oswin
last_name: Aichholzer
- first_name: Hugo A.
full_name: Akitaya, Hugo A.
last_name: Akitaya
- first_name: Kenneth C.
full_name: Cheung, Kenneth C.
last_name: Cheung
- first_name: Erik D.
full_name: Demaine, Erik D.
last_name: Demaine
- first_name: Martin L.
full_name: Demaine, Martin L.
last_name: Demaine
- first_name: Sándor P.
full_name: Fekete, Sándor P.
last_name: Fekete
- first_name: Linda
full_name: Kleist, Linda
last_name: Kleist
- first_name: Irina
full_name: Kostitsyna, Irina
last_name: Kostitsyna
- first_name: Maarten
full_name: Löffler, Maarten
last_name: Löffler
- first_name: Zuzana
full_name: Masárová, Zuzana
id: 45CFE238-F248-11E8-B48F-1D18A9856A87
last_name: Masárová
orcid: 0000-0002-6660-1322
- first_name: Klara
full_name: Mundilova, Klara
last_name: Mundilova
- first_name: Christiane
full_name: Schmidt, Christiane
last_name: Schmidt
citation:
ama: 'Aichholzer O, Akitaya HA, Cheung KC, et al. Folding polyominoes with holes
into a cube. Computational Geometry: Theory and Applications. 2021;93.
doi:10.1016/j.comgeo.2020.101700'
apa: 'Aichholzer, O., Akitaya, H. A., Cheung, K. C., Demaine, E. D., Demaine, M.
L., Fekete, S. P., … Schmidt, C. (2021). Folding polyominoes with holes into a
cube. Computational Geometry: Theory and Applications. Elsevier. https://doi.org/10.1016/j.comgeo.2020.101700'
chicago: 'Aichholzer, Oswin, Hugo A. Akitaya, Kenneth C. Cheung, Erik D. Demaine,
Martin L. Demaine, Sándor P. Fekete, Linda Kleist, et al. “Folding Polyominoes
with Holes into a Cube.” Computational Geometry: Theory and Applications.
Elsevier, 2021. https://doi.org/10.1016/j.comgeo.2020.101700.'
ieee: 'O. Aichholzer et al., “Folding polyominoes with holes into a cube,”
Computational Geometry: Theory and Applications, vol. 93. Elsevier, 2021.'
ista: 'Aichholzer O, Akitaya HA, Cheung KC, Demaine ED, Demaine ML, Fekete SP, Kleist
L, Kostitsyna I, Löffler M, Masárová Z, Mundilova K, Schmidt C. 2021. Folding
polyominoes with holes into a cube. Computational Geometry: Theory and Applications.
93, 101700.'
mla: 'Aichholzer, Oswin, et al. “Folding Polyominoes with Holes into a Cube.” Computational
Geometry: Theory and Applications, vol. 93, 101700, Elsevier, 2021, doi:10.1016/j.comgeo.2020.101700.'
short: 'O. Aichholzer, H.A. Akitaya, K.C. Cheung, E.D. Demaine, M.L. Demaine, S.P.
Fekete, L. Kleist, I. Kostitsyna, M. Löffler, Z. Masárová, K. Mundilova, C. Schmidt,
Computational Geometry: Theory and Applications 93 (2021).'
date_created: 2020-08-30T22:01:09Z
date_published: 2021-02-01T00:00:00Z
date_updated: 2023-08-04T10:57:42Z
day: '01'
department:
- _id: HeEd
doi: 10.1016/j.comgeo.2020.101700
external_id:
arxiv:
- '1910.09917'
isi:
- '000579185100004'
intvolume: ' 93'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1910.09917v3
month: '02'
oa: 1
oa_version: Preprint
project:
- _id: 268116B8-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z00342
name: The Wittgenstein Prize
publication: 'Computational Geometry: Theory and Applications'
publication_identifier:
issn:
- '09257721'
publication_status: published
publisher: Elsevier
quality_controlled: '1'
related_material:
record:
- id: '6989'
relation: shorter_version
status: public
scopus_import: '1'
status: public
title: Folding polyominoes with holes into a cube
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 93
year: '2021'
...
---
_id: '8338'
abstract:
- lang: eng
text: Canonical parametrisations of classical confocal coordinate systems are introduced
and exploited to construct non-planar analogues of incircular (IC) nets on individual
quadrics and systems of confocal quadrics. Intimate connections with classical
deformations of quadrics that are isometric along asymptotic lines and circular
cross-sections of quadrics are revealed. The existence of octahedral webs of surfaces
of Blaschke type generated by asymptotic and characteristic lines that are diagonally
related to lines of curvature is proved theoretically and established constructively.
Appropriate samplings (grids) of these webs lead to three-dimensional extensions
of non-planar IC nets. Three-dimensional octahedral grids composed of planes and
spatially extending (checkerboard) IC-nets are shown to arise in connection with
systems of confocal quadrics in Minkowski space. In this context, the Laguerre
geometric notion of conical octahedral grids of planes is introduced. The latter
generalise the octahedral grids derived from systems of confocal quadrics in Minkowski
space. An explicit construction of conical octahedral grids is presented. The
results are accompanied by various illustrations which are based on the explicit
formulae provided by the theory.
acknowledgement: This research was supported by the DFG Collaborative Research Center
TRR 109 “Discretization in Geometry and Dynamics”. W.K.S. was also supported by
the Australian Research Council (DP1401000851). A.V.A. was also supported by the
European Research Council (ERC) under the European Union’s Horizon 2020 research
and innovation programme (Grant Agreement No. 78818 Alpha).
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Arseniy
full_name: Akopyan, Arseniy
id: 430D2C90-F248-11E8-B48F-1D18A9856A87
last_name: Akopyan
orcid: 0000-0002-2548-617X
- first_name: Alexander I.
full_name: Bobenko, Alexander I.
last_name: Bobenko
- first_name: Wolfgang K.
full_name: Schief, Wolfgang K.
last_name: Schief
- first_name: Jan
full_name: Techter, Jan
last_name: Techter
citation:
ama: Akopyan A, Bobenko AI, Schief WK, Techter J. On mutually diagonal nets on (confocal)
quadrics and 3-dimensional webs. Discrete and Computational Geometry. 2021;66:938-976.
doi:10.1007/s00454-020-00240-w
apa: Akopyan, A., Bobenko, A. I., Schief, W. K., & Techter, J. (2021). On mutually
diagonal nets on (confocal) quadrics and 3-dimensional webs. Discrete and Computational
Geometry. Springer Nature. https://doi.org/10.1007/s00454-020-00240-w
chicago: Akopyan, Arseniy, Alexander I. Bobenko, Wolfgang K. Schief, and Jan Techter.
“On Mutually Diagonal Nets on (Confocal) Quadrics and 3-Dimensional Webs.” Discrete
and Computational Geometry. Springer Nature, 2021. https://doi.org/10.1007/s00454-020-00240-w.
ieee: A. Akopyan, A. I. Bobenko, W. K. Schief, and J. Techter, “On mutually diagonal
nets on (confocal) quadrics and 3-dimensional webs,” Discrete and Computational
Geometry, vol. 66. Springer Nature, pp. 938–976, 2021.
ista: Akopyan A, Bobenko AI, Schief WK, Techter J. 2021. On mutually diagonal nets
on (confocal) quadrics and 3-dimensional webs. Discrete and Computational Geometry.
66, 938–976.
mla: Akopyan, Arseniy, et al. “On Mutually Diagonal Nets on (Confocal) Quadrics
and 3-Dimensional Webs.” Discrete and Computational Geometry, vol. 66,
Springer Nature, 2021, pp. 938–76, doi:10.1007/s00454-020-00240-w.
short: A. Akopyan, A.I. Bobenko, W.K. Schief, J. Techter, Discrete and Computational
Geometry 66 (2021) 938–976.
date_created: 2020-09-06T22:01:13Z
date_published: 2021-10-01T00:00:00Z
date_updated: 2024-03-07T14:51:11Z
day: '01'
department:
- _id: HeEd
doi: 10.1007/s00454-020-00240-w
ec_funded: 1
external_id:
arxiv:
- '1908.00856'
isi:
- '000564488500002'
intvolume: ' 66'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1908.00856
month: '10'
oa: 1
oa_version: Preprint
page: 938-976
project:
- _id: 266A2E9E-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '788183'
name: Alpha Shape Theory Extended
publication: Discrete and Computational Geometry
publication_identifier:
eissn:
- 1432-0444
issn:
- 0179-5376
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: On mutually diagonal nets on (confocal) quadrics and 3-dimensional webs
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 66
year: '2021'
...
---
_id: '8373'
abstract:
- lang: eng
text: It is well known that special Kubo-Ando operator means admit divergence center
interpretations, moreover, they are also mean squared error estimators for certain
metrics on positive definite operators. In this paper we give a divergence center
interpretation for every symmetric Kubo-Ando mean. This characterization of the
symmetric means naturally leads to a definition of weighted and multivariate versions
of a large class of symmetric Kubo-Ando means. We study elementary properties
of these weighted multivariate means, and note in particular that in the special
case of the geometric mean we recover the weighted A#H-mean introduced by Kim,
Lawson, and Lim.
acknowledgement: "The authors are grateful to Milán Mosonyi for fruitful discussions
on the topic, and to the anonymous referee for his/her comments and suggestions.\r\nJ.
Pitrik was supported by the Hungarian Academy of Sciences Lendület-Momentum Grant
for Quantum Information Theory, No. 96 141, and by Hungarian National Research,
Development and Innovation Office (NKFIH) via grants no. K119442, no. K124152, and
no. KH129601. D. Virosztek was supported by the ISTFELLOW program of the Institute
of Science and Technology Austria (project code IC1027FELL01), by the European Union's
Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant
Agreement No. 846294, and partially supported by the Hungarian National Research,
Development and Innovation Office (NKFIH) via grants no. K124152, and no. KH129601."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: József
full_name: Pitrik, József
last_name: Pitrik
- first_name: Daniel
full_name: Virosztek, Daniel
id: 48DB45DA-F248-11E8-B48F-1D18A9856A87
last_name: Virosztek
orcid: 0000-0003-1109-5511
citation:
ama: Pitrik J, Virosztek D. A divergence center interpretation of general symmetric
Kubo-Ando means, and related weighted multivariate operator means. Linear Algebra
and its Applications. 2021;609:203-217. doi:10.1016/j.laa.2020.09.007
apa: Pitrik, J., & Virosztek, D. (2021). A divergence center interpretation
of general symmetric Kubo-Ando means, and related weighted multivariate operator
means. Linear Algebra and Its Applications. Elsevier. https://doi.org/10.1016/j.laa.2020.09.007
chicago: Pitrik, József, and Daniel Virosztek. “A Divergence Center Interpretation
of General Symmetric Kubo-Ando Means, and Related Weighted Multivariate Operator
Means.” Linear Algebra and Its Applications. Elsevier, 2021. https://doi.org/10.1016/j.laa.2020.09.007.
ieee: J. Pitrik and D. Virosztek, “A divergence center interpretation of general
symmetric Kubo-Ando means, and related weighted multivariate operator means,”
Linear Algebra and its Applications, vol. 609. Elsevier, pp. 203–217, 2021.
ista: Pitrik J, Virosztek D. 2021. A divergence center interpretation of general
symmetric Kubo-Ando means, and related weighted multivariate operator means. Linear
Algebra and its Applications. 609, 203–217.
mla: Pitrik, József, and Daniel Virosztek. “A Divergence Center Interpretation of
General Symmetric Kubo-Ando Means, and Related Weighted Multivariate Operator
Means.” Linear Algebra and Its Applications, vol. 609, Elsevier, 2021,
pp. 203–17, doi:10.1016/j.laa.2020.09.007.
short: J. Pitrik, D. Virosztek, Linear Algebra and Its Applications 609 (2021) 203–217.
date_created: 2020-09-11T08:35:50Z
date_published: 2021-01-15T00:00:00Z
date_updated: 2023-08-04T10:58:14Z
day: '15'
department:
- _id: LaEr
doi: 10.1016/j.laa.2020.09.007
ec_funded: 1
external_id:
arxiv:
- '2002.11678'
isi:
- '000581730500011'
intvolume: ' 609'
isi: 1
keyword:
- Kubo-Ando mean
- weighted multivariate mean
- barycenter
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2002.11678
month: '01'
oa: 1
oa_version: Preprint
page: 203-217
project:
- _id: 26A455A6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '846294'
name: Geometric study of Wasserstein spaces and free probability
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Linear Algebra and its Applications
publication_identifier:
issn:
- 0024-3795
publication_status: published
publisher: Elsevier
quality_controlled: '1'
status: public
title: A divergence center interpretation of general symmetric Kubo-Ando means, and
related weighted multivariate operator means
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 609
year: '2021'
...
---
_id: '8429'
abstract:
- lang: eng
text: We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability
estimation, an alternative to marker discovery, and accurate genomic prediction,
taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability
parameters in the UK Biobank. We find that only ≤10% of the genetic variation
captured for height, body mass index, cardiovascular disease, and type 2 diabetes
is attributable to proximal regulatory regions within 10kb upstream of genes,
while 12-25% is attributed to coding regions, 32–44% to introns, and 22-28% to
distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each
chromosome are associated with each trait, with over 3,100 independent exonic
and intronic regions and over 5,400 independent regulatory regions having ≥95%
probability of contributing ≥0.001% to the genetic variance of these four traits.
Our open-source software (GMRM) provides a scalable alternative to current approaches
for biobank data.
acknowledgement: This project was funded by an SNSF Eccellenza Grant to MRR (PCEGP3-181181),
and by core funding from the Institute of Science and Technology Austria. We would
like to thank the participants of the cohort studies, and the Ecole Polytechnique
Federal Lausanne (EPFL) SCITAS for their excellent compute resources, their generosity
with their time and the kindness of their support. P.M.V. acknowledges funding from
the Australian National Health and Medical Research Council (1113400) and the Australian
Research Council (FL180100072). L.R. acknowledges funding from the Kjell & Märta
Beijer Foundation (Stockholm, Sweden). We also would like to acknowledge Simone
Rubinacci, Oliver Delanau, Alexander Terenin, Eleonora Porcu, and Mike Goddard for
their useful comments and suggestions.
article_number: '6972'
article_processing_charge: No
article_type: original
author:
- first_name: Marion
full_name: Patxot, Marion
last_name: Patxot
- first_name: Daniel
full_name: Trejo Banos, Daniel
last_name: Trejo Banos
- first_name: Athanasios
full_name: Kousathanas, Athanasios
last_name: Kousathanas
- first_name: Etienne J
full_name: Orliac, Etienne J
last_name: Orliac
- first_name: Sven E
full_name: Ojavee, Sven E
last_name: Ojavee
- first_name: Gerhard
full_name: Moser, Gerhard
last_name: Moser
- first_name: Julia
full_name: Sidorenko, Julia
last_name: Sidorenko
- first_name: Zoltan
full_name: Kutalik, Zoltan
last_name: Kutalik
- first_name: Reedik
full_name: Magi, Reedik
last_name: Magi
- first_name: Peter M
full_name: Visscher, Peter M
last_name: Visscher
- first_name: Lars
full_name: Ronnegard, Lars
last_name: Ronnegard
- first_name: Matthew Richard
full_name: Robinson, Matthew Richard
id: E5D42276-F5DA-11E9-8E24-6303E6697425
last_name: Robinson
orcid: 0000-0001-8982-8813
citation:
ama: Patxot M, Trejo Banos D, Kousathanas A, et al. Probabilistic inference of the
genetic architecture underlying functional enrichment of complex traits. Nature
Communications. 2021;12(1). doi:10.1038/s41467-021-27258-9
apa: Patxot, M., Trejo Banos, D., Kousathanas, A., Orliac, E. J., Ojavee, S. E.,
Moser, G., … Robinson, M. R. (2021). Probabilistic inference of the genetic architecture
underlying functional enrichment of complex traits. Nature Communications.
Springer Nature. https://doi.org/10.1038/s41467-021-27258-9
chicago: Patxot, Marion, Daniel Trejo Banos, Athanasios Kousathanas, Etienne J Orliac,
Sven E Ojavee, Gerhard Moser, Julia Sidorenko, et al. “Probabilistic Inference
of the Genetic Architecture Underlying Functional Enrichment of Complex Traits.”
Nature Communications. Springer Nature, 2021. https://doi.org/10.1038/s41467-021-27258-9.
ieee: M. Patxot et al., “Probabilistic inference of the genetic architecture
underlying functional enrichment of complex traits,” Nature Communications,
vol. 12, no. 1. Springer Nature, 2021.
ista: Patxot M, Trejo Banos D, Kousathanas A, Orliac EJ, Ojavee SE, Moser G, Sidorenko
J, Kutalik Z, Magi R, Visscher PM, Ronnegard L, Robinson MR. 2021. Probabilistic
inference of the genetic architecture underlying functional enrichment of complex
traits. Nature Communications. 12(1), 6972.
mla: Patxot, Marion, et al. “Probabilistic Inference of the Genetic Architecture
Underlying Functional Enrichment of Complex Traits.” Nature Communications,
vol. 12, no. 1, 6972, Springer Nature, 2021, doi:10.1038/s41467-021-27258-9.
short: M. Patxot, D. Trejo Banos, A. Kousathanas, E.J. Orliac, S.E. Ojavee, G. Moser,
J. Sidorenko, Z. Kutalik, R. Magi, P.M. Visscher, L. Ronnegard, M.R. Robinson,
Nature Communications 12 (2021).
date_created: 2020-09-17T10:52:38Z
date_published: 2021-11-30T00:00:00Z
date_updated: 2023-09-26T10:36:14Z
day: '30'
ddc:
- '610'
department:
- _id: MaRo
doi: 10.1038/s41467-021-27258-9
external_id:
isi:
- '000724450600023'
file:
- access_level: open_access
checksum: 384681be17aff902c149a48f52d13d4f
content_type: application/pdf
creator: cchlebak
date_created: 2021-12-06T07:47:11Z
date_updated: 2021-12-06T07:47:11Z
file_id: '10419'
file_name: 2021_NatComm_Paxtot.pdf
file_size: 6519771
relation: main_file
success: 1
file_date_updated: 2021-12-06T07:47:11Z
has_accepted_license: '1'
intvolume: ' 12'
isi: 1
issue: '1'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
publication: Nature Communications
publication_identifier:
eissn:
- 2041-1723
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '13063'
relation: research_data
status: public
scopus_import: '1'
status: public
title: Probabilistic inference of the genetic architecture underlying functional enrichment
of complex traits
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 12
year: '2021'
...
---
_id: '8430'
abstract:
- lang: eng
text: While recent advancements in computation and modelling have improved the analysis
of complex traits, our understanding of the genetic basis of the time at symptom
onset remains limited. Here, we develop a Bayesian approach (BayesW) that provides
probabilistic inference of the genetic architecture of age-at-onset phenotypes
in a sampling scheme that facilitates biobank-scale time-to-event analyses. We
show in extensive simulation work the benefits BayesW provides in terms of number
of discoveries, model performance and genomic prediction. In the UK Biobank, we
find many thousands of common genomic regions underlying the age-at-onset of high
blood pressure (HBP), cardiac disease (CAD), and type-2 diabetes (T2D), and for
the genetic basis of onset reflecting the underlying genetic liability to disease.
Age-at-menopause and age-at-menarche are also highly polygenic, but with higher
variance contributed by low frequency variants. Genomic prediction into the Estonian
Biobank data shows that BayesW gives higher prediction accuracy than other approaches.
acknowledgement: This project was funded by an SNSF Eccellenza Grant to MRR (PCEGP3-181181),
and by core funding from the Institute of Science and Technology Austria and the
University of Lausanne; the work of KF was supported by the grant PUT1665 by the
Estonian Research Council. We would like to thank Mike Goddard for comments which
greatly improved the work, the participants of the cohort studies, and the Ecole
Polytechnique Federal Lausanne (EPFL) SCITAS for their excellent compute resources,
their generosity with their time and the kindness of their support.
article_number: '2337'
article_processing_charge: No
author:
- first_name: Sven E
full_name: Ojavee, Sven E
last_name: Ojavee
- first_name: Athanasios
full_name: Kousathanas, Athanasios
last_name: Kousathanas
- first_name: Daniel
full_name: Trejo Banos, Daniel
last_name: Trejo Banos
- first_name: Etienne J
full_name: Orliac, Etienne J
last_name: Orliac
- first_name: Marion
full_name: Patxot, Marion
last_name: Patxot
- first_name: Kristi
full_name: Lall, Kristi
last_name: Lall
- first_name: Reedik
full_name: Magi, Reedik
last_name: Magi
- first_name: Krista
full_name: Fischer, Krista
last_name: Fischer
- first_name: Zoltan
full_name: Kutalik, Zoltan
last_name: Kutalik
- first_name: Matthew Richard
full_name: Robinson, Matthew Richard
id: E5D42276-F5DA-11E9-8E24-6303E6697425
last_name: Robinson
orcid: 0000-0001-8982-8813
citation:
ama: Ojavee SE, Kousathanas A, Trejo Banos D, et al. Genomic architecture and prediction
of censored time-to-event phenotypes with a Bayesian genome-wide analysis. Nature
Communications. 2021;12(1). doi:10.1038/s41467-021-22538-w
apa: Ojavee, S. E., Kousathanas, A., Trejo Banos, D., Orliac, E. J., Patxot, M.,
Lall, K., … Robinson, M. R. (2021). Genomic architecture and prediction of censored
time-to-event phenotypes with a Bayesian genome-wide analysis. Nature Communications.
Nature Research. https://doi.org/10.1038/s41467-021-22538-w
chicago: Ojavee, Sven E, Athanasios Kousathanas, Daniel Trejo Banos, Etienne J Orliac,
Marion Patxot, Kristi Lall, Reedik Magi, Krista Fischer, Zoltan Kutalik, and Matthew
Richard Robinson. “Genomic Architecture and Prediction of Censored Time-to-Event
Phenotypes with a Bayesian Genome-Wide Analysis.” Nature Communications.
Nature Research, 2021. https://doi.org/10.1038/s41467-021-22538-w.
ieee: S. E. Ojavee et al., “Genomic architecture and prediction of censored
time-to-event phenotypes with a Bayesian genome-wide analysis,” Nature Communications,
vol. 12, no. 1. Nature Research, 2021.
ista: Ojavee SE, Kousathanas A, Trejo Banos D, Orliac EJ, Patxot M, Lall K, Magi
R, Fischer K, Kutalik Z, Robinson MR. 2021. Genomic architecture and prediction
of censored time-to-event phenotypes with a Bayesian genome-wide analysis. Nature
Communications. 12(1), 2337.
mla: Ojavee, Sven E., et al. “Genomic Architecture and Prediction of Censored Time-to-Event
Phenotypes with a Bayesian Genome-Wide Analysis.” Nature Communications,
vol. 12, no. 1, 2337, Nature Research, 2021, doi:10.1038/s41467-021-22538-w.
short: S.E. Ojavee, A. Kousathanas, D. Trejo Banos, E.J. Orliac, M. Patxot, K. Lall,
R. Magi, K. Fischer, Z. Kutalik, M.R. Robinson, Nature Communications 12 (2021).
date_created: 2020-09-17T10:53:00Z
date_published: 2021-04-20T00:00:00Z
date_updated: 2023-08-04T11:00:17Z
day: '20'
ddc:
- '570'
department:
- _id: MaRo
doi: 10.1038/s41467-021-22538-w
external_id:
isi:
- '000642509600006'
file:
- access_level: open_access
checksum: eca8b9ae713835c5b785211dd08d8a2e
content_type: application/pdf
creator: kschuh
date_created: 2021-05-04T15:07:50Z
date_updated: 2021-05-04T15:07:50Z
file_id: '9372'
file_name: 2021_nature_communications_Ojavee.pdf
file_size: 6474239
relation: main_file
success: 1
file_date_updated: 2021-05-04T15:07:50Z
has_accepted_license: '1'
intvolume: ' 12'
isi: 1
issue: '1'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
project:
- _id: 9B8D11D6-BA93-11EA-9121-9846C619BF3A
grant_number: PCEGP3_181181
name: Improving estimation and prediction of common complex disease risk
publication: Nature Communications
publication_identifier:
eissn:
- '20411723'
publication_status: published
publisher: Nature Research
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/predicting-the-onset-of-diseases/
scopus_import: '1'
status: public
title: Genomic architecture and prediction of censored time-to-event phenotypes with
a Bayesian genome-wide analysis
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 12
year: '2021'
...
---
_id: '8544'
abstract:
- lang: eng
text: The synaptotrophic hypothesis posits that synapse formation stabilizes dendritic
branches, yet this hypothesis has not been causally tested in vivo in the mammalian
brain. Presynaptic ligand cerebellin-1 (Cbln1) and postsynaptic receptor GluD2
mediate synaptogenesis between granule cells and Purkinje cells in the molecular
layer of the cerebellar cortex. Here we show that sparse but not global knockout
of GluD2 causes under-elaboration of Purkinje cell dendrites in the deep molecular
layer and overelaboration in the superficial molecular layer. Developmental, overexpression,
structure-function, and genetic epistasis analyses indicate that dendrite morphogenesis
defects result from competitive synaptogenesis in a Cbln1/GluD2-dependent manner.
A generative model of dendritic growth based on competitive synaptogenesis largely
recapitulates GluD2 sparse and global knockout phenotypes. Our results support
the synaptotrophic hypothesis at initial stages of dendrite development, suggest
a second mode in which cumulative synapse formation inhibits further dendrite
growth, and highlight the importance of competition in dendrite morphogenesis.
acknowledgement: We thank M. Mishina for GluD2fl frozen embryos, T.C. Südhof and J.I.
Morgan for Cbln1fl mice, L. Anderson for help in generating the MADM alleles, W.
Joo for a previously unpublished construct, M. Yuzaki, K. Shen, J. Ding, and members
of the Luo lab, including J.M. Kebschull, H. Li, J. Li, T. Li, C.M. McLaughlin,
D. Pederick, J. Ren, D.C. Wang and C. Xu for discussions and critiques of the manuscript,
and M. Yuzaki for supporting Y.H.T. during the final phase of this project. Y.H.T.
was supported by a JSPS fellowship; S.A.S. was supported by a Stanford Graduate
Fellowship and an NSF Predoctoral Fellowship; L.J. is supported by a Stanford Graduate
Fellowship and an NSF Predoctoral Fellowship; M.J.W. is supported by a Burroughs
Wellcome Fund CASI Award. This work was supported by an NIH grant (R01-NS050538)
to L.L.; the European Research Council (ERC) under the European Union's Horizon
2020 research and innovations programme (No. 725780 LinPro) to S.H.; and Simons
and James S. McDonnell Foundations and an NSF CAREER award to S.G.; L.L. is an HHMI
investigator.
article_processing_charge: No
article_type: original
author:
- first_name: Yukari H.
full_name: Takeo, Yukari H.
last_name: Takeo
- first_name: S. Andrew
full_name: Shuster, S. Andrew
last_name: Shuster
- first_name: Linnie
full_name: Jiang, Linnie
last_name: Jiang
- first_name: Miley
full_name: Hu, Miley
last_name: Hu
- first_name: David J.
full_name: Luginbuhl, David J.
last_name: Luginbuhl
- first_name: Thomas
full_name: Rülicke, Thomas
last_name: Rülicke
- first_name: Ximena
full_name: Contreras, Ximena
id: 475990FE-F248-11E8-B48F-1D18A9856A87
last_name: Contreras
- first_name: Simon
full_name: Hippenmeyer, Simon
id: 37B36620-F248-11E8-B48F-1D18A9856A87
last_name: Hippenmeyer
orcid: 0000-0003-2279-1061
- first_name: Mark J.
full_name: Wagner, Mark J.
last_name: Wagner
- first_name: Surya
full_name: Ganguli, Surya
last_name: Ganguli
- first_name: Liqun
full_name: Luo, Liqun
last_name: Luo
citation:
ama: Takeo YH, Shuster SA, Jiang L, et al. GluD2- and Cbln1-mediated competitive
synaptogenesis shapes the dendritic arbors of cerebellar Purkinje cells. Neuron.
2021;109(4):P629-644.E8. doi:10.1016/j.neuron.2020.11.028
apa: Takeo, Y. H., Shuster, S. A., Jiang, L., Hu, M., Luginbuhl, D. J., Rülicke,
T., … Luo, L. (2021). GluD2- and Cbln1-mediated competitive synaptogenesis shapes
the dendritic arbors of cerebellar Purkinje cells. Neuron. Elsevier. https://doi.org/10.1016/j.neuron.2020.11.028
chicago: Takeo, Yukari H., S. Andrew Shuster, Linnie Jiang, Miley Hu, David J. Luginbuhl,
Thomas Rülicke, Ximena Contreras, et al. “GluD2- and Cbln1-Mediated Competitive
Synaptogenesis Shapes the Dendritic Arbors of Cerebellar Purkinje Cells.” Neuron.
Elsevier, 2021. https://doi.org/10.1016/j.neuron.2020.11.028.
ieee: Y. H. Takeo et al., “GluD2- and Cbln1-mediated competitive synaptogenesis
shapes the dendritic arbors of cerebellar Purkinje cells,” Neuron, vol.
109, no. 4. Elsevier, p. P629–644.E8, 2021.
ista: Takeo YH, Shuster SA, Jiang L, Hu M, Luginbuhl DJ, Rülicke T, Contreras X,
Hippenmeyer S, Wagner MJ, Ganguli S, Luo L. 2021. GluD2- and Cbln1-mediated competitive
synaptogenesis shapes the dendritic arbors of cerebellar Purkinje cells. Neuron.
109(4), P629–644.E8.
mla: Takeo, Yukari H., et al. “GluD2- and Cbln1-Mediated Competitive Synaptogenesis
Shapes the Dendritic Arbors of Cerebellar Purkinje Cells.” Neuron, vol.
109, no. 4, Elsevier, 2021, p. P629–644.E8, doi:10.1016/j.neuron.2020.11.028.
short: Y.H. Takeo, S.A. Shuster, L. Jiang, M. Hu, D.J. Luginbuhl, T. Rülicke, X.
Contreras, S. Hippenmeyer, M.J. Wagner, S. Ganguli, L. Luo, Neuron 109 (2021)
P629–644.E8.
date_created: 2020-09-21T11:59:47Z
date_published: 2021-02-17T00:00:00Z
date_updated: 2024-03-06T12:12:48Z
day: '17'
department:
- _id: SiHi
doi: 10.1016/j.neuron.2020.11.028
ec_funded: 1
intvolume: ' 109'
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/2020.06.14.151258
month: '02'
oa: 1
oa_version: Preprint
page: P629-644.E8
project:
- _id: 260018B0-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '725780'
name: Principles of Neural Stem Cell Lineage Progression in Cerebral Cortex Development
publication: Neuron
publication_identifier:
eissn:
- 1097-4199
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: GluD2- and Cbln1-mediated competitive synaptogenesis shapes the dendritic arbors
of cerebellar Purkinje cells
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 109
year: '2021'
...