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Pratyush Tiwary
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2020 – today
- 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) - [i9]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) - [i8]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) - 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)
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