Computing committors in collective variables via Mahalanobis diffusion maps. - Luke Evans; Maria K. Cameron; Pratyush Tiwary (CoRR, 2021)

Path sampling of recurrent neural networks by incorporating known physics. - Sun-Ting Tsai; Eric Fields; Pratyush Tiwary (CoRR, 2022)

Thermodynamics of Interpretation. - Shams Mehdi; Pratyush Tiwary (CoRR, 2022)

Computing committors via Mahalanobis diffusion maps with enhanced sampling data. - Luke Evans; Maria K. Cameron; Pratyush Tiwary (CoRR, 2022)

Introducing dynamical constraints into representation learning. - Dedi Wang; Yihang Wang; Luke Evans; Pratyush Tiwary (CoRR, 2022)

Enhanced Sampling with Machine Learning: A Review. - Shams Mehdi; Zachary Smith; Lukas Herron; Ziyue Zou; Pratyush Tiwary (CoRR, 2023)

Enhanced sampling of Crystal Nucleation with Graph Representation Learnt Variables. - Ziyue Zou; Pratyush Tiwary (CoRR, 2023)

Generative artificial intelligence for computational chemistry: a roadmap to predicting emergent phenomena. - Pratyush Tiwary; Lukas Herron; Richard John; Suemin Lee; Disha Sanwal; Ruiyu Wang (CoRR, 2024)

Graph Neural Network-State Predictive Information Bottleneck (GNN-SPIB) approach for learning molecular thermodynamics and kinetics. - Ziyue Zou; Dedi Wang; Pratyush Tiwary (CoRR, 2024)

A survey of probabilistic generative frameworks for molecular simulations. - Richard John; Lukas Herron; Pratyush Tiwary (CoRR, 2024)

Graph Attention Site Prediction (GrASP): Identifying Druggable Binding Sites Using Graph Neural Networks with Attention. - Zachary Smith; Michael Strobel; Bodhi P. Vani; Pratyush Tiwary (J. Chem. Inf. Model., 2024)

Exploring Kinase Asp-Phe-Gly (DFG) Loop Conformational Stability with AlphaFold2-RAVE. - Bodhi P. Vani; Akashnathan Aranganathan; Pratyush Tiwary (J. Chem. Inf. Model., 2024)

Latent Thermodynamic Flows: Unified Representation Learning and Generative Modeling of Temperature-Dependent Behaviors from Limited Data. - Yunrui Qiu; Richard John; Lukas Herron; Pratyush Tiwary (CoRR, 2025)