Charles K. Fisher

According to our database, Charles K. Fisher authored at least 16 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

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, Rachel Mak-McCully, Cary Murray, Hanalei Pham, Susanna Qiao, Elena Ryapolova-Webb, Aaron M. Smith, Dimitri Theoharatos, Anil Tolwani, Eric W. Tramel, Anna Vidovszky, Judy Viduya, Jonathan R. Walsh

CoRR, 2024

2023

Neural Boltzmann Machines.

Alex H. Lang, Anton D. Loukianov, Charles K. Fisher

CoRR, 2023

2022

Can RBMs be trained with zero step contrastive divergence?

Charles K. Fisher

CoRR, 2022

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

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

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

2019

Generating Synthetic Control Patients Using Machine Learning for Alzheimer's Disease Clinical Trials.

Charles K. Fisher, Yannick Pouliot, Aaron M. Smith, Jonathan R. Walsh

Proceedings of the AMIA 2019, 2019

2018

Using deep learning for comprehensive, personalized forecasting of Alzheimer's Disease progression.

Charles K. Fisher, Aaron M. Smith, Jonathan R. Walsh

CoRR, 2018

Boltzmann Encoded Adversarial Machines.

Charles K. Fisher, Aaron M. Smith, Jonathan R. Walsh

CoRR, 2018

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

2017

Variable habitat conditions drive species covariation in the human microbiota.

Charles K. Fisher, Thierry Mora, Aleksandra M. Walczak

PLoS Comput. Biol., 2017

2015

Bayesian Feature Selection with Strongly Regularizing Priors Maps to the Ising Model.

Charles K. Fisher, Pankaj Mehta

Neural Comput., 2015

Bayesian feature selection for high-dimensional linear regression via the Ising approximation with applications to genomics.

Charles K. Fisher, Pankaj Mehta

Bioinform., 2015

2014

Fast Bayesian Feature Selection for High Dimensional Linear Regression in Genomics via the Ising Approximation.

Charles K. Fisher, Pankaj Mehta

CoRR, 2014

Variational Pseudolikelihood for Regularized Ising Inference.

Charles K. Fisher

CoRR, 2014

2012

Efficient Construction of Disordered Protein Ensembles in a Bayesian Framework with Optimal Selection of Conformations.

Charles K. Fisher, Orly Ullman, Collin M. Stultz

Proceedings of the Biocomputing 2012: Proceedings of the Pacific Symposium, 2012