Efficient Construction of Disordered Protein Ensembles in a Bayesian Framework with Optimal Selection of Conformations. - Charles K. Fisher; Orly Ullman; Collin M. Stultz (Pacific Symposium on Biocomputing, 2012)

Variational Pseudolikelihood for Regularized Ising Inference. - Charles K. Fisher (CoRR, 2014)

Fast Bayesian Feature Selection for High Dimensional Linear Regression in Genomics via the Ising Approximation. - Charles K. Fisher; Pankaj Mehta (CoRR, 2014)

Bayesian feature selection for high-dimensional linear regression via the Ising approximation with applications to genomics. - Charles K. Fisher; Pankaj Mehta (Bioinform., 2015)

Bayesian Feature Selection with Strongly Regularizing Priors Maps to the Ising Model. - Charles K. Fisher; Pankaj Mehta (Neural Comput., 2015)

Variable habitat conditions drive species covariation in the human microbiota. - Charles K. Fisher; Thierry Mora; Aleksandra M. Walczak (PLoS Comput. Biol., 2017)

A high-bias, low-variance introduction to Machine Learning for physicists. - Pankaj Mehta; Marin Bukov; Ching-Hao Wang; Alexandre G. R. Day; Clint Richardson; Charles K. Fisher; David J. Schwab (CoRR, 2018)

Boltzmann Encoded Adversarial Machines. - Charles K. Fisher; Aaron M. Smith; Jonathan R. Walsh (CoRR, 2018)

Using deep learning for comprehensive, personalized forecasting of Alzheimer's Disease progression. - Charles K. Fisher; Aaron M. Smith; Jonathan R. Walsh (CoRR, 2018)

Generating Synthetic Control Patients Using Machine Learning for Alzheimer's Disease Clinical Trials. - Charles K. Fisher; Yannick Pouliot; Aaron M. Smith; Jonathan R. Walsh (AMIA, 2019)

Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data. - Aaron M. Smith; Jonathan R. Walsh; John Long; Craig B. Davis; Peter Henstock; Martin R. Hodge; Mateusz Maciejewski; Xinmeng Jasmine Mu; Stephen Ra; Shanrong Zhao; Daniel Ziemek; Charles K. Fisher (BMC Bioinform., 2020)

Generating Digital Twins with Multiple Sclerosis Using Probabilistic Neural Networks. - Jonathan R. Walsh; Aaron M. Smith; Yannick Pouliot; David Li-Bland; Anton Loukianov; Charles K. Fisher (CoRR, 2020)

Modeling Disease Progression in Mild Cognitive Impairment and Alzheimer's Disease with Digital Twins. - Daniele Bertolini; Anton D. Loukianov; Aaron M. Smith; David Li-Bland; Yannick Pouliot; Jonathan R. Walsh; Charles K. Fisher (CoRR, 2020)

Can RBMs be trained with zero step contrastive divergence? - Charles K. Fisher (CoRR, 2022)

Neural Boltzmann Machines. - Alex H. Lang; Anton D. Loukianov; Charles K. Fisher (CoRR, 2023)

Digital Twin Generators for Disease Modeling. - Nameyeh Alam; Jake Basilico; Daniele Bertolini; Satish Casie Chetty; Heather D'Angelo; Ryan Douglas; Charles K. Fisher; Franklin Fuller; Melissa Gomes; Rishabh Gupta; Alex H. Lang; Anton Loukianov; et al. (CoRR, 2024)