@inproceedings{193,
  abstract     = {We show attacks on five data-independent memory-hard functions (iMHF) that were submitted to the password hashing competition (PHC). Informally, an MHF is a function which cannot be evaluated on dedicated hardware, like ASICs, at significantly lower hardware and/or energy cost than evaluating a single instance on a standard single-core architecture. Data-independent means the memory access pattern of the function is independent of the input; this makes iMHFs harder to construct than data-dependent ones, but the latter can be attacked by various side-channel attacks. Following [Alwen-Blocki'16], we capture the evaluation of an iMHF as a directed acyclic graph (DAG). The cumulative parallel pebbling complexity of this DAG is a measure for the hardware cost of evaluating the iMHF on an ASIC. Ideally, one would like the complexity of a DAG underlying an iMHF to be as close to quadratic in the number of nodes of the graph as possible. Instead, we show that (the DAGs underlying) the following iMHFs are far from this bound: Rig.v2, TwoCats and Gambit each having an exponent no more than 1.75. Moreover, we show that the complexity of the iMHF modes of the PHC finalists Pomelo and Lyra2 have exponents at most 1.83 and 1.67 respectively. To show this we investigate a combinatorial property of each underlying DAG (called its depth-robustness. By establishing upper bounds on this property we are then able to apply the general technique of [Alwen-Block'16] for analyzing the hardware costs of an iMHF.},
  author       = {Alwen, Joel F and Gazi, Peter and Kamath Hosdurg, Chethan and Klein, Karen and Osang, Georg F and Pietrzak, Krzysztof Z and Reyzin, Lenoid and Rolinek, Michal and Rybar, Michal},
  booktitle    = {Proceedings of the 2018 on Asia Conference on Computer and Communication Security},
  location     = {Incheon, Republic of Korea},
  pages        = {51 -- 65},
  publisher    = {ACM},
  title        = {{On the memory hardness of data independent password hashing functions}},
  doi          = {10.1145/3196494.3196534},
  year         = {2018},
}

@article{194,
  abstract     = {Ants are emerging model systems to study cellular signaling because distinct castes possess different physiologic phenotypes within the same colony. Here we studied the functionality of inotocin signaling, an insect ortholog of mammalian oxytocin (OT), which was recently discovered in ants. In Lasius ants, we determined that specialization within the colony, seasonal factors, and physiologic conditions down-regulated the expression of the OT-like signaling system. Given this natural variation, we interrogated its function using RNAi knockdowns. Next-generation RNA sequencing of OT-like precursor knock-down ants highlighted its role in the regulation of genes involved in metabolism. Knock-down ants exhibited higher walking activity and increased self-grooming in the brood chamber. We propose that OT-like signaling in ants is important for regulating metabolic processes and locomotion.},
  author       = {Liutkeviciute, Zita and Gil Mansilla, Esther and Eder, Thomas and Casillas Perez, Barbara E and Giulia Di Giglio, Maria and Muratspahić, Edin and Grebien, Florian and Rattei, Thomas and Muttenthaler, Markus and Cremer, Sylvia and Gruber, Christian},
  issn         = {08926638},
  journal      = {The FASEB Journal},
  number       = {12},
  pages        = {6808--6821},
  publisher    = {FASEB},
  title        = {{Oxytocin-like signaling in ants influences metabolic gene expression and locomotor activity}},
  doi          = {10.1096/fj.201800443},
  volume       = {32},
  year         = {2018},
}

@article{195,
  abstract     = {We demonstrate that identical impurities immersed in a two-dimensional many-particle bath can be viewed as flux-tube-charged-particle composites described by fractional statistics. In particular, we find that the bath manifests itself as an external magnetic flux tube with respect to the impurities, and hence the time-reversal symmetry is broken for the effective Hamiltonian describing the impurities. The emerging flux tube acts as a statistical gauge field after a certain critical coupling. This critical coupling corresponds to the intersection point between the quasiparticle state and the phonon wing, where the angular momentum is transferred from the impurity to the bath. This amounts to a novel configuration with emerging anyons. The proposed setup paves the way to realizing anyons using electrons interacting with superfluid helium or lattice phonons, as well as using atomic impurities in ultracold gases.},
  author       = {Yakaboylu, Enderalp and Lemeshko, Mikhail},
  journal      = {Physical Review B - Condensed Matter and Materials Physics},
  number       = {4},
  publisher    = {American Physical Society},
  title        = {{Anyonic statistics of quantum impurities in two dimensions}},
  doi          = {10.1103/PhysRevB.98.045402},
  volume       = {98},
  year         = {2018},
}

@phdthesis{197,
  abstract     = {Modern computer vision systems heavily rely on statistical machine learning models, which typically require large amounts of labeled data to be learned reliably. Moreover, very recently computer vision research widely adopted techniques for representation learning, which further increase the demand for labeled data. However, for many important practical problems there is relatively small amount of labeled data available, so it is problematic to leverage full potential of the representation learning methods. One way to overcome this obstacle is to invest substantial resources into producing large labelled datasets. Unfortunately, this can be prohibitively expensive in practice. In this thesis we focus on the alternative way of tackling the aforementioned issue. We concentrate on methods, which make use of weakly-labeled or even unlabeled data. Specifically, the first half of the thesis is dedicated to the semantic image segmentation task. We develop a technique, which achieves competitive segmentation performance and only requires annotations in a form of global image-level labels instead of dense segmentation masks. Subsequently, we present a new methodology, which further improves segmentation performance by leveraging tiny additional feedback from a human annotator. By using our methods practitioners can greatly reduce the amount of data annotation effort, which is required to learn modern image segmentation models. In the second half of the thesis we focus on methods for learning from unlabeled visual data. We study a family of autoregressive models for modeling structure of natural images and discuss potential applications of these models. Moreover, we conduct in-depth study of one of these applications, where we develop the state-of-the-art model for the probabilistic image colorization task.},
  author       = {Kolesnikov, Alexander},
  issn         = {2663-337X},
  pages        = {113},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images}},
  doi          = {10.15479/AT:ISTA:th_1021},
  year         = {2018},
}

@article{198,
  abstract     = {We consider a class of students learning a language from a teacher. The situation can be interpreted as a group of child learners receiving input from the linguistic environment. The teacher provides sample sentences. The students try to learn the grammar from the teacher. In addition to just listening to the teacher, the students can also communicate with each other. The students hold hypotheses about the grammar and change them if they receive counter evidence. The process stops when all students have converged to the correct grammar. We study how the time to convergence depends on the structure of the classroom by introducing and evaluating various complexity measures. We find that structured communication between students, although potentially introducing confusion, can greatly reduce some of the complexity measures. Our theory can also be interpreted as applying to the scientific process, where nature is the teacher and the scientists are the students.},
  author       = {Ibsen-Jensen, Rasmus and Tkadlec, Josef and Chatterjee, Krishnendu and Nowak, Martin},
  issn         = {1742-5662},
  journal      = {Journal of the Royal Society Interface},
  number       = {140},
  publisher    = {The Royal Society},
  title        = {{Language acquisition with communication between learners}},
  doi          = {10.1098/rsif.2018.0073},
  volume       = {15},
  year         = {2018},
}

@article{199,
  abstract     = {Sex-biased genes are central to the study of sexual selection, sexual antagonism, and sex chromosome evolution. We describe a comprehensive de novo assembled transcriptome in the common frog Rana temporaria based on five developmental stages and three adult tissues from both sexes, obtained from a population with karyotypically homomorphic but genetically differentiated sex chromosomes. This allows the study of sex-biased gene expression throughout development, and its effect on the rate of gene evolution while accounting for pleiotropic expression, which is known to negatively correlate with the evolutionary rate. Overall, sex-biased genes had little overlap among developmental stages and adult tissues. Late developmental stages and gonad tissues had the highest numbers of stage-or tissue-specific genes. We find that pleiotropic gene expression is a better predictor than sex bias for the evolutionary rate of genes, though it often interacts with sex bias. Although genetically differentiated, the sex chromosomes were not enriched in sex-biased genes, possibly due to a very recent arrest of XY recombination. These results extend our understanding of the developmental dynamics, tissue specificity, and genomic localization of sex-biased genes.},
  author       = {Ma, Wen and Veltsos, Paris and Toups, Melissa A and Rodrigues, Nicolas and Sermier, Roberto and Jeffries, Daniel and Perrin, Nicolas},
  journal      = {Genes},
  number       = {6},
  publisher    = {MDPI AG},
  title        = {{Tissue specificity and dynamics of sex biased gene expression in a common frog population with differentiated, yet homomorphic, sex chromosomes}},
  doi          = {10.3390/genes9060294},
  volume       = {9},
  year         = {2018},
}

@article{2,
  abstract     = {Indirect reciprocity explores how humans act when their reputation is at stake, and which social norms they use to assess the actions of others. A crucial question in indirect reciprocity is which social norms can maintain stable cooperation in a society. Past research has highlighted eight such norms, called “leading-eight” strategies. This past research, however, is based on the assumption that all relevant information about other population members is publicly available and that everyone agrees on who is good or bad. Instead, here we explore the reputation dynamics when information is private and noisy. We show that under these conditions, most leading-eight strategies fail to evolve. Those leading-eight strategies that do evolve are unable to sustain full cooperation.Indirect reciprocity is a mechanism for cooperation based on shared moral systems and individual reputations. It assumes that members of a community routinely observe and assess each other and that they use this information to decide who is good or bad, and who deserves cooperation. When information is transmitted publicly, such that all community members agree on each other’s reputation, previous research has highlighted eight crucial moral systems. These “leading-eight” strategies can maintain cooperation and resist invasion by defectors. However, in real populations individuals often hold their own private views of others. Once two individuals disagree about their opinion of some third party, they may also see its subsequent actions in a different light. Their opinions may further diverge over time. Herein, we explore indirect reciprocity when information transmission is private and noisy. We find that in the presence of perception errors, most leading-eight strategies cease to be stable. Even if a leading-eight strategy evolves, cooperation rates may drop considerably when errors are common. Our research highlights the role of reliable information and synchronized reputations to maintain stable moral systems.},
  author       = {Hilbe, Christian and Schmid, Laura and Tkadlec, Josef and Chatterjee, Krishnendu and Nowak, Martin},
  journal      = {PNAS},
  number       = {48},
  pages        = {12241--12246},
  publisher    = {National Academy of Sciences},
  title        = {{Indirect reciprocity with private, noisy, and incomplete information}},
  doi          = {10.1073/pnas.1810565115},
  volume       = {115},
  year         = {2018},
}

@article{20,
  abstract     = {Background: Norepinephrine (NE) signaling has a key role in white adipose tissue (WAT) functions, including lipolysis, free fatty acid liberation and, under certain conditions, conversion of white into brite (brown-in-white) adipocytes. However, acute effects of NE stimulation have not been described at the transcriptional network level. Results: We used RNA-seq to uncover a broad transcriptional response. The inference of protein-protein and protein-DNA interaction networks allowed us to identify a set of immediate-early genes (IEGs) with high betweenness, validating our approach and suggesting a hierarchical control of transcriptional regulation. In addition, we identified a transcriptional regulatory network with IEGs as master regulators, including HSF1 and NFIL3 as novel NE-induced IEG candidates. Moreover, a functional enrichment analysis and gene clustering into functional modules suggest a crosstalk between metabolic, signaling, and immune responses. Conclusions: Altogether, our network biology approach explores for the first time the immediate-early systems level response of human adipocytes to acute sympathetic activation, thereby providing a first network basis of early cell fate programs and crosstalks between metabolic and transcriptional networks required for proper WAT function.},
  author       = {Higareda Almaraz, Juan and Karbiener, Michael and Giroud, Maude and Pauler, Florian and Gerhalter, Teresa and Herzig, Stephan and Scheideler, Marcel},
  issn         = {1471-2164},
  journal      = {BMC Genomics},
  number       = {1},
  publisher    = {BioMed Central},
  title        = {{Norepinephrine triggers an immediate-early regulatory network response in primary human white adipocytes}},
  doi          = {10.1186/s12864-018-5173-0},
  volume       = {19},
  year         = {2018},
}

@phdthesis{200,
  abstract     = {This thesis is concerned with the inference of current population structure based on geo-referenced genetic data. The underlying idea is that population structure affects its spatial genetic structure. Therefore, genotype information can be utilized to estimate important demographic parameters such as migration rates. These indirect estimates of population structure have become very attractive, as genotype data is now widely available. However, there also has been much concern about these approaches. Importantly, genetic structure can be influenced by many complex patterns, which often cannot be disentangled. Moreover, many methods merely fit heuristic patterns of genetic structure, and do not build upon population genetics theory. Here, I describe two novel inference methods that address these shortcomings. In Chapter 2, I introduce an inference scheme based on a new type of signal, identity by descent (IBD) blocks. Recently, it has become feasible to detect such long blocks of genome shared between pairs of samples. These blocks are direct traces of recent coalescence events. As such, they contain ample signal for inferring recent demography. I examine sharing of IBD blocks in two-dimensional populations with local migration. Using a diffusion approximation, I derive formulas for an isolation by distance pattern of long IBD blocks and show that sharing of long IBD blocks approaches rapid exponential decay for growing sample distance. I describe an inference scheme based on these results. It can robustly estimate the dispersal rate and population density, which is demonstrated on simulated data. I also show an application to estimate mean migration and the rate of recent population growth within Eastern Europe. Chapter 3 is about a novel method to estimate barriers to gene flow in a two dimensional population. This inference scheme utilizes geographically localized allele frequency fluctuations - a classical isolation by distance signal. The strength of these local fluctuations increases on average next to a barrier, and there is less correlation across it. I again use a framework of diffusion of ancestral lineages to model this effect, and provide an efficient numerical implementation to fit the results to geo-referenced biallelic SNP data. This inference scheme is able to robustly estimate strong barriers to gene flow, as tests on simulated data confirm.},
  author       = {Ringbauer, Harald},
  issn         = {2663-337X},
  pages        = {146},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Inferring recent demography from spatial genetic structure}},
  doi          = {10.15479/AT:ISTA:th_963},
  year         = {2018},
}

@phdthesis{201,
  abstract     = {We describe arrangements of three-dimensional spheres from a geometrical and topological point of view. Real data (fitting this setup) often consist of soft spheres which show certain degree of deformation while strongly packing against each other. In this context, we answer the following questions: If we model a soft packing of spheres by hard spheres that are allowed to overlap, can we measure the volume in the overlapped areas? Can we be more specific about the overlap volume, i.e. quantify how much volume is there covered exactly twice, three times, or k times? What would be a good optimization criteria that rule the arrangement of soft spheres while making a good use of the available space? Fixing a particular criterion, what would be the optimal sphere configuration? The first result of this thesis are short formulas for the computation of volumes covered by at least k of the balls. The formulas exploit information contained in the order-k Voronoi diagrams and its closely related Level-k complex. The used complexes lead to a natural generalization into poset diagrams, a theoretical formalism that contains the order-k and degree-k diagrams as special cases. In parallel, we define different criteria to determine what could be considered an optimal arrangement from a geometrical point of view. Fixing a criterion, we find optimal soft packing configurations in 2D and 3D where the ball centers lie on a lattice. As a last step, we use tools from computational topology on real physical data, to show the potentials of higher-order diagrams in the description of melting crystals. The results of the experiments leaves us with an open window to apply the theories developed in this thesis in real applications.},
  author       = {Iglesias Ham, Mabel},
  issn         = {2663-337X},
  pages        = {171},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Multiple covers with balls}},
  doi          = {10.15479/AT:ISTA:th_1026},
  year         = {2018},
}

@article{203,
  abstract     = {Asymmetric auxin distribution is instrumental for the differential growth that causes organ bending on tropic stimuli and curvatures during plant development. Local differences in auxin concentrations are achieved mainly by polarized cellular distribution of PIN auxin transporters, but whether other mechanisms involving auxin homeostasis are also relevant for the formation of auxin gradients is not clear. Here we show that auxin methylation is required for asymmetric auxin distribution across the hypocotyl, particularly during its response to gravity. We found that loss-of-function mutants in Arabidopsis IAA CARBOXYL METHYLTRANSFERASE1 (IAMT1) prematurely unfold the apical hook, and that their hypocotyls are impaired in gravitropic reorientation. This defect is linked to an auxin-dependent increase in PIN gene expression, leading to an increased polar auxin transport and lack of asymmetric distribution of PIN3 in the iamt1 mutant. Gravitropic reorientation in the iamt1 mutant could be restored with either endodermis-specific expression of IAMT1 or partial inhibition of polar auxin transport, which also results in normal PIN gene expression levels. We propose that IAA methylation is necessary in gravity-sensing cells to restrict polar auxin transport within the range of auxin levels that allow for differential responses.},
  author       = {Abbas, Mohamad and Hernández, García J and Pollmann, Stephan and Samodelov, Sophia L and Kolb, Martina and Friml, Jirí and Hammes, Ulrich Z and Zurbriggen, Matias D and Blázquez, Miguel and Alabadí, David},
  journal      = {PNAS},
  number       = {26},
  pages        = {6864--6869},
  publisher    = {National Academy of Sciences},
  title        = {{Auxin methylation is required for differential growth in Arabidopsis}},
  doi          = {10.1073/pnas.1806565115},
  volume       = {115},
  year         = {2018},
}

@article{134,
  abstract     = {The current state of the art in real-time two-dimensional water wave simulation requires developers to choose between efficient Fourier-based methods, which lack interactions with moving obstacles, and finite-difference or finite element methods, which handle environmental interactions but are significantly more expensive. This paper attempts to bridge this long-standing gap between complexity and performance, by proposing a new wave simulation method that can faithfully simulate wave interactions with moving obstacles in real time while simultaneously preserving minute details and accommodating very large simulation domains.

Previous methods for simulating 2D water waves directly compute the change in height of the water surface, a strategy which imposes limitations based on the CFL condition (fast moving waves require small time steps) and Nyquist's limit (small wave details require closely-spaced simulation variables). This paper proposes a novel wavelet transformation that discretizes the liquid motion in terms of amplitude-like functions that vary over space, frequency, and direction, effectively generalizing Fourier-based methods to handle local interactions. Because these new variables change much more slowly over space than the original water height function, our change of variables drastically reduces the limitations of the CFL condition and Nyquist limit, allowing us to simulate highly detailed water waves at very large visual resolutions. Our discretization is amenable to fast summation and easy to parallelize. We also present basic extensions like pre-computed wave paths and two-way solid fluid coupling. Finally, we argue that our discretization provides a convenient set of variables for artistic manipulation, which we illustrate with a novel wave-painting interface.},
  author       = {Jeschke, Stefan and Skrivan, Tomas and Mueller Fischer, Matthias and Chentanez, Nuttapong and Macklin, Miles and Wojtan, Christopher J},
  journal      = {ACM Transactions on Graphics},
  number       = {4},
  publisher    = {ACM},
  title        = {{Water surface wavelets}},
  doi          = {10.1145/3197517.3201336},
  volume       = {37},
  year         = {2018},
}

@article{135,
  abstract     = {The Fluid Implicit Particle method (FLIP) reduces numerical dissipation by combining particles with grids. To improve performance, the subsequent narrow band FLIP method (NB‐FLIP) uses a FLIP‐based fluid simulation only near the liquid surface and a traditional grid‐based fluid simulation away from the surface. This spatially‐limited FLIP simulation significantly reduces the number of particles and alleviates a computational bottleneck. In this paper, we extend the NB‐FLIP idea even further, by allowing a simulation to transition between a FLIP‐like fluid simulation and a grid‐based simulation in arbitrary locations, not just near the surface. This approach leads to even more savings in memory and computation, because we can concentrate the particles only in areas where they are needed. More importantly, this new method allows us to seamlessly transition to smooth implicit surface geometry wherever the particle‐based simulation is unnecessary. Consequently, our method leads to a practical algorithm for avoiding the noisy surface artifacts associated with particle‐based liquid simulations, while simultaneously maintaining the benefits of a FLIP simulation in regions of dynamic motion.},
  author       = {Sato, Takahiro and Wojtan, Christopher J and Thuerey, Nils and Igarashi, Takeo and Ando, Ryoichi},
  issn         = {0167-7055},
  journal      = {Computer Graphics Forum},
  number       = {2},
  pages        = {169 -- 177},
  publisher    = {Wiley},
  title        = {{Extended narrow band FLIP for liquid simulations}},
  doi          = {10.1111/cgf.13351},
  volume       = {37},
  year         = {2018},
}

@article{136,
  abstract     = {Recent studies suggest that unstable, nonchaotic solutions of the Navier-Stokes equation may provide deep insights into fluid turbulence. In this article, we present a combined experimental and numerical study exploring the dynamical role of unstable equilibrium solutions and their invariant manifolds in a weakly turbulent, electromagnetically driven, shallow fluid layer. Identifying instants when turbulent evolution slows down, we compute 31 unstable equilibria of a realistic two-dimensional model of the flow. We establish the dynamical relevance of these unstable equilibria by showing that they are closely visited by the turbulent flow. We also establish the dynamical relevance of unstable manifolds by verifying that they are shadowed by turbulent trajectories departing from the neighborhoods of unstable equilibria over large distances in state space.},
  author       = {Suri, Balachandra and Tithof, Jeffrey and Grigoriev, Roman and Schatz, Michael},
  journal      = {Physical Review E},
  number       = {2},
  publisher    = {American Physical Society},
  title        = {{Unstable equilibria and invariant manifolds in quasi-two-dimensional Kolmogorov-like flow}},
  doi          = {10.1103/PhysRevE.98.023105},
  volume       = {98},
  year         = {2018},
}

@article{137,
  abstract     = {Fluorescent sensors are an essential part of the experimental toolbox of the life sciences, where they are used ubiquitously to visualize intra- and extracellular signaling. In the brain, optical neurotransmitter sensors can shed light on temporal and spatial aspects of signal transmission by directly observing, for instance, neurotransmitter release and spread. Here we report the development and application of the first optical sensor for the amino acid glycine, which is both an inhibitory neurotransmitter and a co-agonist of the N-methyl-d-aspartate receptors (NMDARs) involved in synaptic plasticity. Computational design of a glycine-specific binding protein allowed us to produce the optical glycine FRET sensor (GlyFS), which can be used with single and two-photon excitation fluorescence microscopy. We took advantage of this newly developed sensor to test predictions about the uneven spatial distribution of glycine in extracellular space and to demonstrate that extracellular glycine levels are controlled by plasticity-inducing stimuli.},
  author       = {Zhang, William and Herde, Michel and Mitchell, Joshua and Whitfield, Jason and Wulff, Andreas and Vongsouthi, Vanessa and Sanchez Romero, Inmaculada and Gulakova, Polina and Minge, Daniel and Breithausen, Björn and Schoch, Susanne and Janovjak, Harald L and Jackson, Colin and Henneberger, Christian},
  journal      = {Nature Chemical Biology},
  number       = {9},
  pages        = {861 -- 869},
  publisher    = {Nature Publishing Group},
  title        = {{Monitoring hippocampal glycine with the computationally designed optical sensor GlyFS}},
  doi          = {10.1038/s41589-018-0108-2},
  volume       = {14},
  year         = {2018},
}

@article{139,
  abstract     = {Genome-scale diversity data are increasingly available in a variety of biological systems, and can be used to reconstruct the past evolutionary history of species divergence. However, extracting the full demographic information from these data is not trivial, and requires inferential methods that account for the diversity of coalescent histories throughout the genome. Here, we evaluate the potential and limitations of one such approach. We reexamine a well-known system of mussel sister species, using the joint site frequency spectrum (jSFS) of synonymousmutations computed either fromexome capture or RNA-seq, in an Approximate Bayesian Computation (ABC) framework. We first assess the best sampling strategy (number of: individuals, loci, and bins in the jSFS), and show that model selection is robust to variation in the number of individuals and loci. In contrast, different binning choices when summarizing the jSFS, strongly affect the results: including classes of low and high frequency shared polymorphisms can more effectively reveal recent migration events. We then take advantage of the flexibility of ABC to compare more realistic models of speciation, including variation in migration rates through time (i.e., periodic connectivity) and across genes (i.e., genome-wide heterogeneity in migration rates). We show that these models were consistently selected as the most probable, suggesting that mussels have experienced a complex history of gene flow during divergence and that the species boundary is semi-permeable. Our work provides a comprehensive evaluation of ABC demographic inference in mussels based on the coding jSFS, and supplies guidelines for employing different sequencing techniques and sampling strategies. We emphasize, perhaps surprisingly, that inferences are less limited by the volume of data, than by the way in which they are analyzed.},
  author       = {Fraisse, Christelle and Roux, Camille and Gagnaire, Pierre and Romiguier, Jonathan and Faivre, Nicolas and Welch, John and Bierne, Nicolas},
  journal      = {PeerJ},
  number       = {7},
  publisher    = {PeerJ},
  title        = {{The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: The effects of sequencing techniques and sampling strategies}},
  doi          = {10.7717/peerj.5198},
  volume       = {2018},
  year         = {2018},
}

@article{14,
  abstract     = {The intercellular transport of auxin is driven by PIN-formed (PIN) auxin efflux carriers. PINs are localized at the plasma membrane (PM) and on constitutively recycling endomembrane vesicles. Therefore, PINs can mediate auxin transport either by direct translocation across the PM or by pumping auxin into secretory vesicles (SVs), leading to its secretory release upon fusion with the PM. Which of these two mechanisms dominates is a matter of debate. Here, we addressed the issue with a mathematical modeling approach. We demonstrate that the efficiency of secretory transport depends on SV size, half-life of PINs on the PM, pH, exocytosis frequency and PIN density. 3D structured illumination microscopy (SIM) was used to determine PIN density on the PM. Combining this data with published values of the other parameters, we show that the transport activity of PINs in SVs would have to be at least 1000× greater than on the PM in order to produce a comparable macroscopic auxin transport. If both transport mechanisms operated simultaneously and PINs were equally active on SVs and PM, the contribution of secretion to the total auxin flux would be negligible. In conclusion, while secretory vesicle-mediated transport of auxin is an intriguing and theoretically possible model, it is unlikely to be a major mechanism of auxin transport inplanta.},
  author       = {Hille, Sander and Akhmanova, Maria and Glanc, Matous and Johnson, Alexander J and Friml, Jirí},
  issn         = {1422-0067},
  journal      = {International Journal of Molecular Sciences},
  number       = {11},
  publisher    = {MDPI},
  title        = {{Relative contribution of PIN-containing secretory vesicles and plasma membrane PINs to the directed auxin transport: Theoretical estimation}},
  doi          = {10.3390/ijms19113566},
  volume       = {19},
  year         = {2018},
}

@inproceedings{140,
  abstract     = {Reachability analysis is difficult for hybrid automata with affine differential equations, because the reach set needs to be approximated. Promising abstraction techniques usually employ interval methods or template polyhedra. Interval methods account for dense time and guarantee soundness, and there are interval-based tools that overapproximate affine flowpipes. But interval methods impose bounded and rigid shapes, which make refinement expensive and fixpoint detection difficult. Template polyhedra, on the other hand, can be adapted flexibly and can be unbounded, but sound template refinement for unbounded reachability analysis has been implemented only for systems with piecewise constant dynamics. We capitalize on the advantages of both techniques, combining interval arithmetic and template polyhedra, using the former to abstract time and the latter to abstract space. During a CEGAR loop, whenever a spurious error trajectory is found, we compute additional space constraints and split time intervals, and use these space-time interpolants to eliminate the counterexample. Space-time interpolation offers a lazy, flexible framework for increasing precision while guaranteeing soundness, both for error avoidance and fixpoint detection. To the best of out knowledge, this is the first abstraction refinement scheme for the reachability analysis over unbounded and dense time of affine hybrid systems, which is both sound and automatic. We demonstrate the effectiveness of our algorithm with several benchmark examples, which cannot be handled by other tools.},
  author       = {Frehse, Goran and Giacobbe, Mirco and Henzinger, Thomas A},
  issn         = {03029743},
  location     = {Oxford, United Kingdom},
  pages        = {468 -- 486},
  publisher    = {Springer},
  title        = {{Space-time interpolants}},
  doi          = {10.1007/978-3-319-96145-3_25},
  volume       = {10981},
  year         = {2018},
}

@inproceedings{141,
  abstract     = {Given a model and a specification, the fundamental model-checking problem asks for algorithmic verification of whether the model satisfies the specification. We consider graphs and Markov decision processes (MDPs), which are fundamental models for reactive systems. One of the very basic specifications that arise in verification of reactive systems is the strong fairness (aka Streett) objective. Given different types of requests and corresponding grants, the objective requires that for each type, if the request event happens infinitely often, then the corresponding grant event must also happen infinitely often. All ω -regular objectives can be expressed as Streett objectives and hence they are canonical in verification. To handle the state-space explosion, symbolic algorithms are required that operate on a succinct implicit representation of the system rather than explicitly accessing the system. While explicit algorithms for graphs and MDPs with Streett objectives have been widely studied, there has been no improvement of the basic symbolic algorithms. The worst-case numbers of symbolic steps required for the basic symbolic algorithms are as follows: quadratic for graphs and cubic for MDPs. In this work we present the first sub-quadratic symbolic algorithm for graphs with Streett objectives, and our algorithm is sub-quadratic even for MDPs. Based on our algorithmic insights we present an implementation of the new symbolic approach and show that it improves the existing approach on several academic benchmark examples.},
  author       = {Chatterjee, Krishnendu and Henzinger, Monika H and Loitzenbauer, Veronika and Oraee, Simin and Toman, Viktor},
  location     = {Oxford, United Kingdom},
  pages        = {178--197},
  publisher    = {Springer},
  title        = {{Symbolic algorithms for graphs and Markov decision processes with fairness objectives}},
  doi          = {10.1007/978-3-319-96142-2_13},
  volume       = {10982},
  year         = {2018},
}

@inproceedings{14198,
  abstract     = {High-dimensional time series are common in many domains. Since human
cognition is not optimized to work well in high-dimensional spaces, these areas
could benefit from interpretable low-dimensional representations. However, most
representation learning algorithms for time series data are difficult to
interpret. This is due to non-intuitive mappings from data features to salient
properties of the representation and non-smoothness over time. To address this
problem, we propose a new representation learning framework building on ideas
from interpretable discrete dimensionality reduction and deep generative
modeling. This framework allows us to learn discrete representations of time
series, which give rise to smooth and interpretable embeddings with superior
clustering performance. We introduce a new way to overcome the
non-differentiability in discrete representation learning and present a
gradient-based version of the traditional self-organizing map algorithm that is
more performant than the original. Furthermore, to allow for a probabilistic
interpretation of our method, we integrate a Markov model in the representation
space. This model uncovers the temporal transition structure, improves
clustering performance even further and provides additional explanatory
insights as well as a natural representation of uncertainty. We evaluate our
model in terms of clustering performance and interpretability on static
(Fashion-)MNIST data, a time series of linearly interpolated (Fashion-)MNIST
images, a chaotic Lorenz attractor system with two macro states, as well as on
a challenging real world medical time series application on the eICU data set.
Our learned representations compare favorably with competitor methods and
facilitate downstream tasks on the real world data.},
  author       = {Fortuin, Vincent and Hüser, Matthias and Locatello, Francesco and Strathmann, Heiko and Rätsch, Gunnar},
  booktitle    = {International Conference on Learning Representations},
  location     = {New Orleans, LA, United States},
  title        = {{SOM-VAE: Interpretable discrete representation learning on time series}},
  year         = {2018},
}

