@inbook{7410, abstract = {Epiboly is a conserved gastrulation movement describing the thinning and spreading of a sheet or multi-layer of cells. The zebrafish embryo has emerged as a vital model system to address the cellular and molecular mechanisms that drive epiboly. In the zebrafish embryo, the blastoderm, consisting of a simple squamous epithelium (the enveloping layer) and an underlying mass of deep cells, as well as a yolk nuclear syncytium (the yolk syncytial layer) undergo epiboly to internalize the yolk cell during gastrulation. The major events during zebrafish epiboly are: expansion of the enveloping layer and the internal yolk syncytial layer, reduction and removal of the yolk membrane ahead of the advancing blastoderm margin and deep cell rearrangements between the enveloping layer and yolk syncytial layer to thin the blastoderm. Here, work addressing the cellular and molecular mechanisms as well as the sources of the mechanical forces that underlie these events is reviewed. The contribution of recent findings to the current model of epiboly as well as open questions and future prospects are also discussed.}, author = {Bruce, Ashley E.E. and Heisenberg, Carl-Philipp J}, booktitle = {Gastrulation: From Embryonic Pattern to Form}, editor = {Solnica-Krezel, Lilianna }, isbn = {9780128127988}, issn = {0070-2153}, pages = {319--341}, publisher = {Elsevier}, title = {{Mechanisms of zebrafish epiboly: A current view}}, doi = {10.1016/bs.ctdb.2019.07.001}, volume = {136}, year = {2020}, } @article{6944, abstract = {We study the problem of automatically detecting if a given multi-class classifier operates outside of its specifications (out-of-specs), i.e. on input data from a different distribution than what it was trained for. This is an important problem to solve on the road towards creating reliable computer vision systems for real-world applications, because the quality of a classifier’s predictions cannot be guaranteed if it operates out-of-specs. Previously proposed methods for out-of-specs detection make decisions on the level of single inputs. This, however, is insufficient to achieve low false positive rate and high false negative rates at the same time. In this work, we describe a new procedure named KS(conf), based on statistical reasoning. Its main component is a classical Kolmogorov–Smirnov test that is applied to the set of predicted confidence values for batches of samples. Working with batches instead of single samples allows increasing the true positive rate without negatively affecting the false positive rate, thereby overcoming a crucial limitation of single sample tests. We show by extensive experiments using a variety of convolutional network architectures and datasets that KS(conf) reliably detects out-of-specs situations even under conditions where other tests fail. It furthermore has a number of properties that make it an excellent candidate for practical deployment: it is easy to implement, adds almost no overhead to the system, works with any classifier that outputs confidence scores, and requires no a priori knowledge about how the data distribution could change.}, author = {Sun, Rémy and Lampert, Christoph}, issn = {1573-1405}, journal = {International Journal of Computer Vision}, number = {4}, pages = {970--995}, publisher = {Springer Nature}, title = {{KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications}}, doi = {10.1007/s11263-019-01232-x}, volume = {128}, year = {2020}, } @inproceedings{8324, abstract = {The notion of program sensitivity (aka Lipschitz continuity) specifies that changes in the program input result in proportional changes to the program output. For probabilistic programs the notion is naturally extended to expected sensitivity. A previous approach develops a relational program logic framework for proving expected sensitivity of probabilistic while loops, where the number of iterations is fixed and bounded. In this work, we consider probabilistic while loops where the number of iterations is not fixed, but randomized and depends on the initial input values. We present a sound approach for proving expected sensitivity of such programs. Our sound approach is martingale-based and can be automated through existing martingale-synthesis algorithms. Furthermore, our approach is compositional for sequential composition of while loops under a mild side condition. We demonstrate the effectiveness of our approach on several classical examples from Gambler's Ruin, stochastic hybrid systems and stochastic gradient descent. We also present experimental results showing that our automated approach can handle various probabilistic programs in the literature.}, author = {Wang, Peixin and Fu, Hongfei and Chatterjee, Krishnendu and Deng, Yuxin and Xu, Ming}, booktitle = {Proceedings of the ACM on Programming Languages}, issn = {2475-1421}, number = {POPL}, publisher = {ACM}, title = {{Proving expected sensitivity of probabilistic programs with randomized variable-dependent termination time}}, doi = {10.1145/3371093}, volume = {4}, year = {2020}, } @article{7160, abstract = {Nocturnal animals that rely on their visual system for foraging, mating, and navigation usually exhibit specific traits associated with living in scotopic conditions. Most nocturnal birds have several visual specializations, such as enlarged eyes and an increased orbital convergence. However, the actual role of binocular vision in nocturnal foraging is still debated. Nightjars (Aves: Caprimulgidae) are predators that actively pursue and capture flying insects in crepuscular and nocturnal environments, mainly using a conspicuous “sit-and-wait” tactic on which pursuit begins with an insect flying over the bird that sits on the ground. In this study, we describe the visual system of the band-winged nightjar (Systellura longirostris), with emphasis on anatomical features previously described as relevant for nocturnal birds. Orbit convergence, determined by 3D scanning of the skull, was 73.28°. The visual field, determined by ophthalmoscopic reflex, exhibits an area of maximum binocular overlap of 42°, and it is dorsally oriented. The eyes showed a nocturnal-like normalized corneal aperture/axial length index. Retinal ganglion cells (RGCs) were relatively scant, and distributed in an unusual oblique-band pattern, with higher concentrations in the ventrotemporal quadrant. Together, these results indicate that the band-winged nightjar exhibits a retinal specialization associated with the binocular area of their dorsal visual field, a relevant area for pursuit triggering and prey attacks. The RGC distribution observed is unusual among birds, but similar to that of some visually dependent insectivorous bats, suggesting that those features might be convergent in relation to feeding strategies.}, author = {Salazar, Juan Esteban and Severin, Daniel and Vega Zuniga, Tomas A and Fernández-Aburto, Pedro and Deichler, Alfonso and Sallaberry A., Michel and Mpodozis, Jorge}, issn = {1421-9743}, journal = {Brain, Behavior and Evolution}, number = {1-4}, pages = {27--36}, publisher = {Karger Publishers}, title = {{Anatomical specializations related to foraging in the visual system of a nocturnal insectivorous bird, the band-winged nightjar (Aves: Caprimulgiformes)}}, doi = {10.1159/000504162}, volume = {94}, year = {2020}, } @article{6184, abstract = {We prove edge universality for a general class of correlated real symmetric or complex Hermitian Wigner matrices with arbitrary expectation. Our theorem also applies to internal edges of the self-consistent density of states. In particular, we establish a strong form of band rigidity which excludes mismatches between location and label of eigenvalues close to internal edges in these general models.}, author = {Alt, Johannes and Erdös, László and Krüger, Torben H and Schröder, Dominik J}, issn = {0091-1798}, journal = {Annals of Probability}, number = {2}, pages = {963--1001}, publisher = {Institute of Mathematical Statistics}, title = {{Correlated random matrices: Band rigidity and edge universality}}, doi = {10.1214/19-AOP1379}, volume = {48}, year = {2020}, }