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2020 – today
- 2024
[i11]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:
Digital Twin Generators for Disease Modeling. CoRR abs/2405.01488 (2024)- 2023
- [i10]Alex H. Lang, Anton D. Loukianov, Charles K. Fisher:
Neural Boltzmann Machines. CoRR abs/2305.08337 (2023) - 2022
- [i9]Charles K. Fisher:
Can RBMs be trained with zero step contrastive divergence? CoRR abs/2211.02174 (2022) - 2020
- [j4]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:
Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data. BMC Bioinform. 21(1): 119 (2020) - [i8]Jonathan R. Walsh, Aaron M. Smith, Yannick Pouliot, David Li-Bland, Anton Loukianov, Charles K. Fisher:
Generating Digital Twins with Multiple Sclerosis Using Probabilistic Neural Networks. CoRR abs/2002.02779 (2020) - [i7]Daniele Bertolini, Anton D. Loukianov, Aaron M. Smith, David Li-Bland, Yannick Pouliot, Jonathan R. Walsh, Charles K. Fisher:
Modeling Disease Progression in Mild Cognitive Impairment and Alzheimer's Disease with Digital Twins. CoRR abs/2012.13455 (2020)
2010 – 2019
- 2019
- [c2]Charles K. Fisher, Yannick Pouliot, Aaron M. Smith, Jonathan R. Walsh:
Generating Synthetic Control Patients Using Machine Learning for Alzheimer's Disease Clinical Trials. AMIA 2019 - 2018
- [i6]Pankaj Mehta, Marin Bukov, Ching-Hao Wang, Alexandre G. R. Day, Clint Richardson, Charles K. Fisher, David J. Schwab:
A high-bias, low-variance introduction to Machine Learning for physicists. CoRR abs/1803.08823 (2018) - [i5]Charles K. Fisher, Aaron M. Smith, Jonathan R. Walsh:
Boltzmann Encoded Adversarial Machines. CoRR abs/1804.08682 (2018) - [i4]Charles K. Fisher, Aaron M. Smith, Jonathan R. Walsh:
Using deep learning for comprehensive, personalized forecasting of Alzheimer's Disease progression. CoRR abs/1807.03876 (2018) - 2017
- [j3]Charles K. Fisher, Thierry Mora, Aleksandra M. Walczak:
Variable habitat conditions drive species covariation in the human microbiota. PLoS Comput. Biol. 13(4) (2017) - 2015
- [j2]Charles K. Fisher, Pankaj Mehta:
Bayesian feature selection for high-dimensional linear regression via the Ising approximation with applications to genomics. Bioinform. 31(11): 1754-1761 (2015) - [j1]Charles K. Fisher, Pankaj Mehta:
Bayesian Feature Selection with Strongly Regularizing Priors Maps to the Ising Model. Neural Comput. 27(11): 2411-2422 (2015) - 2014
- [i3]Charles K. Fisher, Pankaj Mehta:
Fast Bayesian Feature Selection for High Dimensional Linear Regression in Genomics via the Ising Approximation. CoRR abs/1407.8187 (2014) - [i2]Charles K. Fisher:
Variational Pseudolikelihood for Regularized Ising Inference. CoRR abs/1409.7074 (2014) - [i1]Charles K. Fisher, Pankaj Mehta:
Bayesian feature selection with strongly-regularizing priors maps to the Ising Model. CoRR abs/1411.0591 (2014) - 2012
- [c1]Charles K. Fisher, Orly Ullman, Collin M. Stultz:
Efficient Construction of Disordered Protein Ensembles in a Bayesian Framework with Optimal Selection of Conformations. Pacific Symposium on Biocomputing 2012: 82-93
Coauthor Index
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