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Neurons in the dorsal subregion of the medial superior temporal (MSTd) area respond to large, complex patterns of retinal flow, implying a role in the analysis of self-motion. Some neurons are selective for the expanding radial motion that…

Neurons and Cognition · Quantitative Biology 2017-02-24 Michael Beyeler , Nikil Dutt , Jeffrey L. Krichmar

It is well known that the calculated cosmological constant, when regularized with a cutoff, differs hugely from the measured value. These calculations are made on the basis of a wave-vector cut-off that is usually set at the Planck scale.…

High Energy Physics - Theory · Physics 2026-03-31 Satish Ramakrishna

Two main seismic features characterize the Earth's inner core: a North-South polar anisotropy and an East-West asymmetry of P-wave velocity and attenuation. Anisotropy is expected if shear deformation is induced by convective motions.…

Geophysics · Physics 2015-06-04 Hugau Mizzon , Marc Monnereau

Data augmentation is one of the most widely used techniques to improve generalization in modern machine learning, often justified by its ability to promote invariance to label-irrelevant transformations. However, its theoretical role…

Machine Learning · Computer Science 2026-02-17 Abdelali Bouyahia , Frédéric LeBlanc , Mario Marchand

Light traveling through the vacuum interacts with vacuum fluctuations similarly to the way that light traveling through a dielectric interacts with ordinary matter. And just as the permittivity of a dielectric can be calculated, the…

General Physics · Physics 2026-02-17 G. B. Mainland , Bernard Mulligan

Previously, in (Hermundstad et al., 2014), we showed that when sampling is limiting, the efficient coding principle leads to a "variance is salience" hypothesis, and that this hypothesis accounts for visual sensitivity to binary image…

Neurons and Cognition · Quantitative Biology 2020-07-14 Tiberiu Tesileanu , Mary M. Conte , John J. Briguglio , Ann M. Hermundstad , Jonathan D. Victor , Vijay Balasubramanian

Learning representations that capture the underlying data generating process is a key problem for data efficient and robust use of neural networks. One key property for robustness which the learned representation should capture and which…

Machine Learning · Computer Science 2022-06-24 Mathieu Chevalley , Charlotte Bunne , Andreas Krause , Stefan Bauer

We revisit the theory of importance weighted variational inference (IWVI), a promising strategy for learning latent variable models. IWVI uses new variational bounds, known as Monte Carlo objectives (MCOs), obtained by replacing intractable…

Machine Learning · Statistics 2022-01-27 Pierre-Alexandre Mattei , Jes Frellsen

Vision Transformers (ViTs) achieve strong data-driven scaling by leveraging all-to-all self-attention. However, this flexibility incurs a computational cost that scales quadratically with image resolution, limiting ViTs in high-resolution…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Alan Z. Song , Yinjie Chen , Mu Nan , Rui Zhang , Jiahang Cao , Weijian Mai , Muquan Yu , Hossein Adeli , Deva Ramanan , Michael J. Tarr , Andrew F. Luo

Our formal understanding of the inductive bias that drives the success of convolutional networks on computer vision tasks is limited. In particular, it is unclear what makes hypotheses spaces born from convolution and pooling operations so…

Neural and Evolutionary Computing · Computer Science 2017-04-19 Nadav Cohen , Amnon Shashua

Variational inference approximates Bayesian posterior distributions by projecting onto a tractable family of distributions. While most theoretical analyses evaluate the quality of this approximation using global divergence measures, many…

Statistics Theory · Mathematics 2026-03-11 Sean Plummer

Deep convolutional neural networks trained for image object categorization have shown remarkable similarities with representations found across the primate ventral visual stream. Yet, artificial and biological networks still exhibit…

Computer Vision and Pattern Recognition · Computer Science 2019-06-12 Alex Hernández-García , Peter König , Tim C. Kietzmann

Learning features invariant to arbitrary transformations in the data is a requirement for any recognition system, biological or artificial. It is now widely accepted that simple cells in the primary visual cortex respond to features while…

Neural and Evolutionary Computing · Computer Science 2020-12-14 Jayanta K. Dutta , Bonny Banerjee

This paper covers the material of our two talks. We describe a series of projects based upon perturbative expansions to follow the gravitational evolution of the one point probability distribution functions (PDFs) for the density contrast…

Astrophysics · Physics 2007-05-23 F. R. Bouchet , R. Juszkiewicz

Accurate medical image segmentation is an integral part of the medical image analysis pipeline that requires the ability to merge local and global information. While vision transformers are able to capture global interactions using vanilla…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Elisha Dayag , Nhat Thanh Tran , Jack Xin

Heterotic M-Theory is a promising candidate for that corner of M-theory which makes contact with the real world. However, while the theory requires one of its expansion parameters, $\epsilon$, to be perturbatively small, a successful…

High Energy Physics - Theory · Physics 2010-04-05 Gottfried Curio , Axel Krause

A model of particle production is developed based on a parallel with a theory of Bose-Einstein condensation and similarities with other critical phenomena such as critical opalescence. The role of a power law critical exponent tau and Levy…

Nuclear Theory · Physics 2008-11-26 A. Z. Mekjian , T. Csorgo , S. Hegyi

The visual crowding makes it difficult to identify the patterns in peripheral vision, but the neural mechanism for this phenomenon is still unclear because of different opinions. In order to study the separation effect of V1 under different…

Neurons and Cognition · Quantitative Biology 2019-05-27 Xieyi Liu , Junjun Zhang , Ling Li

Spatiotemporal sensitivity to high frequency information declines with increased peripheral eccentricity. Foveated rendering exploits this by decreasing the spatial resolution of rendered images in peripheral vision, reducing the rendering…

Visual estimation of heading in the human brain is widely believed to be based on instantaneous optic flow, the velocity of retinal image motion. However, we previously found that humans are unable to use instantaneous optic flow to…

Neurons and Cognition · Quantitative Biology 2022-04-28 Charlie S. Burlingham , Mengjian Hua , Oliver Xu , Kathryn Bonnen , David J. Heeger
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