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We investigate the problem of designing optimal classifiers in the strategic classification setting, where the classification is part of a game in which players can modify their features to attain a favorable classification outcome (while…

Machine Learning · Computer Science 2020-05-19 Mark Braverman , Sumegha Garg

The modal factor model represents a new factor model for dimension reduction in high dimensional panel data. Unlike the approximate factor model that targets for the mean factors, it captures factors that influence the conditional mode of…

Econometrics · Economics 2024-10-01 Zhe Sun , Yundong Tu

Epithelial tissues play a fundamental role in various morphogenetic events during development and early embryogenesis. Although epithelial monolayers are often modeled as two-dimensional (2D) elastic surfaces, they distinguish themselves…

Soft Condensed Matter · Physics 2020-06-15 Benjamin Loewe , Francesco Serafin , Suraj Shankar , Mark J. Bowick , M. Cristina Marchetti

Coordinated cellular movements are key processes in tissue morphogenesis. Using a cell-based modeling approach we study the dynamics of epithelial layers lining surfaces with constant and varying curvature. We demonstrate that extrinsic…

Soft Condensed Matter · Physics 2024-03-21 Lea Happel , Axel Voigt

This paper investigates a family of dynamical systems arising from an evolutionary re-interpretation of certain optimal control and optimization problems. We focus particularly on the application in image registration of the theory of…

Chaotic Dynamics · Physics 2011-06-21 F. Gay-Balmaz , D. D. Holm , T. S. Ratiu

Evolutionary algorithms offer great promise for the automatic design of robot bodies, tailoring them to specific environments or tasks. Most research is done on simplified models or virtual robots in physics simulators, which do not capture…

Robotics · Computer Science 2020-05-20 Tonnes F. Nygaard , David Howard , Kyrre Glette

Parameter estimation is of fundamental importance in areas from atomic spectroscopy and atomic clocks to gravitational wave detection. Entangled probes provide a significant precision gain over classical strategies in the absence of noise.…

Quantum Physics · Physics 2013-10-28 R. Chaves , J. B. Brask , M. Markiewicz , J. Kolodynski , A. Acin

Embedding 3D morphable basis functions into deep neural networks opens great potential for models with better representation power. However, to faithfully learn those models from an image collection, it requires strong regularization to…

Computer Vision and Pattern Recognition · Computer Science 2019-04-11 Luan Tran , Feng Liu , Xiaoming Liu

Mining and learning the shape variability of underlying population has benefited the applications including parametric shape modeling, 3D animation, and image segmentation. The current statistical shape modeling method works well on…

Computer Vision and Pattern Recognition · Computer Science 2020-06-09 Xilu Wang

A macroscopic theory for describing cellular states during steady-growth is presented, which is based on the consistency between cellular growth and molecular replication, as well as the robustness of phenotypes against perturbations.…

Populations and Evolution · Quantitative Biology 2021-02-08 Kunihiko Kaneko , Chikara Furusawa

This paper describes an Artificial Embryology method (called ``Epigenetic Tracking'') to generate predefined arbitrarily shaped 2-dimensional arrays of cells by means of evolutionary techniques. It is based on a model of development, whose…

Adaptation and Self-Organizing Systems · Physics 2008-05-19 Alessandro Fontana

A large variety of real systems are composed by entities in relationships which can be represented by networks. In many of these systems, elements are embedded in the space and location information impacts properties and evolution. Local…

Physics and Society · Physics 2021-11-09 Michele Tirico , Stefan Balev , Antoine Dutot , Damien Olivier

In naturalistic learning problems, a model's input contains a wide range of features, some useful for the task at hand, and others not. Of the useful features, which ones does the model use? Of the task-irrelevant features, which ones does…

Machine Learning · Computer Science 2020-10-26 Katherine L. Hermann , Andrew K. Lampinen

We consider a statistical model for matrix factorization in a regime where the rank of the two hidden matrix factors grows linearly with their dimension and their product is corrupted by additive noise. Despite various approaches,…

Information Theory · Computer Science 2023-06-08 Farzad Pourkamali , Nicolas Macris

The answers to many unsolved problems lie in the intractable chemical space of molecules and materials. Machine learning techniques are rapidly growing in popularity as a way to compress and explore chemical space efficiently. One of the…

Chemical Physics · Physics 2020-01-06 John E. Herr , Kevin Koh , Kun Yao , John Parkhill

Competition between individuals drives the evolution of whole species. Although the fittest individuals survive the longest and produce the most offspring, in some circumstances the resulting species may not be optimally fit. Here, using…

Populations and Evolution · Quantitative Biology 2015-09-24 Tim Rogers , Alan J. McKane

Effects of the inhomogeneous matter density on the three-generation neutrino oscillation probability are analyzed. Realistic profile of the matter density is expanded into a Fourier series. Taking in the Fourier modes one by one, we…

High Energy Physics - Phenomenology · Physics 2016-06-22 Masafumi Koike , Toshihiko Ota , Masako Saito , Joe Sato

Epigenetic Tracking is a mathematical model of biological cells, originally conceived to study embryonic development. Computer simulations proved the capacity of the model to generate complex 3-dimensional cellular structures, and the…

Cell Behavior · Quantitative Biology 2015-07-07 Alessandro Fontana

Noise is source of ambiguity for fuzzy systems. Although being an important aspect, the effects of noise in fuzzy modeling have been little investigated. This paper presents a set of tests using three well-known fuzzy modeling algorithms.…

Neural and Evolutionary Computing · Computer Science 2007-05-23 P. J. Costa Branco , J. A. Dente

During embryonic development tissue morphogenesis and signaling are tightly coupled. It is therefore important to simulate both tissue morphogenesis and signaling simultaneously in in silico models of developmental processes. The resolution…

Tissues and Organs · Quantitative Biology 2013-05-28 Dagmar Iber , Simon Tanaka , Patrick Fried , Philipp Germann , Denis Menshykau