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Pratyush Tiwary
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2020 – today
- 2025
[i12]Yunrui Qiu, Richard John, Lukas Herron, Pratyush Tiwary:
Latent Thermodynamic Flows: Unified Representation Learning and Generative Modeling of Temperature-Dependent Behaviors from Limited Data. CoRR abs/2507.03174 (2025)
[i11]Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille Bilodeau, Keith Brown, Emmanuel Candes, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutiérrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang:
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR abs/2509.02661 (2025)- 2024
[j2]Zachary Smith, Michael Strobel, Bodhi P. Vani
, Pratyush Tiwary
:
Graph Attention Site Prediction (GrASP): Identifying Druggable Binding Sites Using Graph Neural Networks with Attention. J. Chem. Inf. Model. 64(7): 2637-2644 (2024)
[j1]Bodhi P. Vani
, Akashnathan Aranganathan
, Pratyush Tiwary
:
Exploring Kinase Asp-Phe-Gly (DFG) Loop Conformational Stability with AlphaFold2-RAVE. J. Chem. Inf. Model. 64(7): 2789-2797 (2024)
[i10]Pratyush Tiwary, Lukas Herron, Richard John, Suemin Lee, Disha Sanwal, Ruiyu Wang
:
Generative artificial intelligence for computational chemistry: a roadmap to predicting emergent phenomena. CoRR abs/2409.03118 (2024)
[i9]Ziyue Zou, Dedi Wang, Pratyush Tiwary:
Graph Neural Network-State Predictive Information Bottleneck (GNN-SPIB) approach for learning molecular thermodynamics and kinetics. CoRR abs/2409.11843 (2024)
[i8]Richard John, Lukas Herron, Pratyush Tiwary:
A survey of probabilistic generative frameworks for molecular simulations. CoRR abs/2411.09388 (2024)- 2023
[i7]Shams Mehdi, Zachary Smith, Lukas Herron, Ziyue Zou, Pratyush Tiwary:
Enhanced Sampling with Machine Learning: A Review. CoRR abs/2306.09111 (2023)
[i6]Ziyue Zou, Pratyush Tiwary:
Enhanced sampling of Crystal Nucleation with Graph Representation Learnt Variables. CoRR abs/2310.07927 (2023)- 2022
[i5]Sun-Ting Tsai, Eric Fields, Pratyush Tiwary:
Path sampling of recurrent neural networks by incorporating known physics. CoRR abs/2203.00597 (2022)
[i4]Shams Mehdi, Pratyush Tiwary:
Thermodynamics of Interpretation. CoRR abs/2206.13475 (2022)
[i3]Luke Evans, Maria K. Cameron, Pratyush Tiwary:
Computing committors via Mahalanobis diffusion maps with enhanced sampling data. CoRR abs/2208.13772 (2022)
[i2]Dedi Wang, Yihang Wang
, Luke Evans, Pratyush Tiwary:
Introducing dynamical constraints into representation learning. CoRR abs/2209.00905 (2022)- 2021
[i1]Luke Evans, Maria K. Cameron, Pratyush Tiwary:
Computing committors in collective variables via Mahalanobis diffusion maps. CoRR abs/2108.08979 (2021)
Coauthor Index

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