| Discovering symbolic policies with deep reinforcement learning M Landajuela, BK Petersen, S Kim, CP Santiago, R Glatt, N Mundhenk, ... International Conference on Machine Learning, 5979-5989, 2021 | 91 | 2021 |
| Taxonomies of cyber adversaries and attacks: a survey of incidents and approaches CA Meyers, SS Powers, DM Faissol Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2009 | 83 | 2009 |
| Symbolic regression via neural-guided genetic programming population seeding TN Mundhenk, M Landajuela, R Glatt, CP Santiago, DM Faissol, ... arXiv preprint arXiv:2111.00053, 2021 | 69 | 2021 |
| Deep reinforcement learning and simulation as a path toward precision medicine BK Petersen, J Yang, WS Grathwohl, C Cockrell, C Santiago, G An, ... Journal of Computational Biology 26 (6), 597-604, 2019 | 52 | 2019 |
| Single episode policy transfer in reinforcement learning J Yang, B Petersen, H Zha, D Faissol arXiv preprint arXiv:1910.07719, 2019 | 37 | 2019 |
| Precision medicine as a control problem: Using simulation and deep reinforcement learning to discover adaptive, personalized multi-cytokine therapy for sepsis BK Petersen, J Yang, WS Grathwohl, C Cockrell, C Santiago, G An, ... arXiv preprint arXiv:1802.10440, 2018 | 31 | 2018 |
| Reinforcement learning for adaptive mesh refinement J Yang, T Dzanic, B Petersen, J Kudo, K Mittal, V Tomov, JS Camier, ... International Conference on Artificial Intelligence and Statistics, 5997-6014, 2023 | 30 | 2023 |
| Rapid in silico design of antibodies targeting SARS-CoV-2 using machine learning and supercomputing T Desautels, A Zemla, E Lau, M Franco, D Faissol BioRxiv, 2020.04. 03.024885, 2020 | 29 | 2020 |
| Timing of testing and treatment for asymptomatic diseases E Kırkızlar, DM Faissol, PM Griffin, JL Swann Mathematical biosciences 226 (1), 28-37, 2010 | 25 | 2010 |
| Bias in Markov models of disease DM Faissol, PM Griffin, JL Swann Mathematical biosciences 220 (2), 143-156, 2009 | 17 | 2009 |
| Timing of testing and treatment of hepatitis C and other diseases DM Faissol, PM Griffin, JL Swann Proceedings, 11, 2007 | 14 | 2007 |
| Improving exploration in policy gradient search: Application to symbolic optimization M Landajuela, BK Petersen, SK Kim, CP Santiago, R Glatt, TN Mundhenk, ... arXiv preprint arXiv:2107.09158, 2021 | 13 | 2021 |
| Large-scale application of free energy perturbation calculations for antibody design F Zhu, FA Bourguet, WFD Bennett, EY Lau, KT Arrildt, BW Segelke, ... Scientific Reports 12 (1), 12489, 2022 | 12 | 2022 |
| The role of bathhouses and sex clubs in HIV transmission: findings from a mathematic model DM Faissol, JL Swann, B Kolodziejski, PM Griffin, TL Gift JAIDS Journal of Acquired Immune Deficiency Syndromes 44 (4), 386-394, 2007 | 12 | 2007 |
| Exploitation of ambiguous cues to infer terrorist activity KS Ni, D Faissol, T Edmunds, R Wheeler Decision Analysis 10 (1), 42-62, 2013 | 9 | 2013 |
| Probabilistic Characterization of Adversary Behavior in Cyber Security CA Meyers, SS Powers, DM Faissol Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2009 | 8 | 2009 |
| AbBERT: learning antibody humanness via masked language modeling D Vashchenko, S Nguyen, A Goncalves, FL da Silva, B Petersen, ... bioRxiv, 2022.08. 02.502236, 2022 | 7 | 2022 |
| Learning sparse symbolic policies for sepsis treatment JF Pettit, BK Petersen, FL Silva, DB Larie, RC Cockrell, G An, DM Faissol Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2021 | 7 | 2021 |
| Multi-agent reinforcement learning for adaptive mesh refinement J Yang, K Mittal, T Dzanic, S Petrides, B Keith, B Petersen, D Faissol, ... arXiv preprint arXiv:2211.00801, 2022 | 6 | 2022 |
| SARS-COV-2 Omicron variant predicted to exhibit higher affinity to ACE-2 receptor and lower affinity to a large range of neutralizing antibodies, using a rapid computational … A Zemla, T Desautels, EY Lau, F Zhu, KT Arrildt, BW Segelke, ... bioRxiv, 2021.12. 16.472843, 2021 | 4 | 2021 |
