932 citations · 3.1k across the 40 of their papers we have counts for
7 papers · 1 filter
Bayesian feature selection with strongly-regularizing priors maps to the Ising Model
Charles K. Fisher, Pankaj Mehta
Identifying small subsets of features that are relevant for prediction and/or classification tasks is a central problem in machine learning and statistics. The feature selection ta…
An exact mapping between the Variational Renormalization Group and Deep Learning
Pankaj Mehta, David J. Schwab
Deep learning is a broad set of techniques that uses multiple layers of representation to automatically learn relevant features directly from structured data. Recently, such techni…
Fast Bayesian Feature Selection for High Dimensional Linear Regression in Genomics via the Ising Approximation
Charles K. Fisher, Pankaj Mehta
Feature selection, identifying a subset of variables that are relevant for predicting a response, is an important and challenging component of many methods in statistics and machin…
Multiscale modeling of oscillations and spiral waves in Dictyostelium populations
Javad Noorbakhsh, David Schwab, Allyson Sgro +2
Unicellular organisms exhibit elaborate collective behaviors in response to environmental cues. These behaviors are controlled by complex biochemical networks within individual cel…
From Intracellular Signaling to Population Oscillations: Bridging Scales in Collective Behavior
Allyson E. Sgro, David J. Schwab, Javad Noorbakhsh +3
Collective behavior in cellular populations is coordinated by biochemical signaling networks within individual cells. Connecting the dynamics of these intracellular networks to the…
Thermodynamics of statistical inference by cells
Alex H. Lang, Charles K. Fisher, Thierry Mora +1
The deep connection between thermodynamics, computation, and information is now well established both theoretically and experimentally. Here, we extend these ideas to show that the…