Saee Gopal Paliwal

According to our database, Saee Gopal Paliwal authored at least 16 papers between 2014 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Fold-CP: A Context Parallelism Framework for Biomolecular Modeling.

Dejun Lin, Simon K. S. Chu, Vishanth Iyer, Youhan Lee, John St. John, Kevin Boyd, Brian Roland, Xiaowei Ren, Guoqing Zhou, Zhonglin Cao, Polina Binder, Yuliya Zhautouskaya, Jakub Zakrzewski, Maximilian Stadler, Kyle Gion, Yuxing Peng, Xi Chen, Tianjing Zhang, Philipp Junk, Michelle Dimon, Pawel Gniewek, Fabian Ortega, McKinley Polen, Ivan Grubisic, Ali Bashir, Graham Holt, Danny Kovtun, Matthias Grass, Luca Naef, Rui Wang, Jian Peng, Anthony B. Costa, Saee Paliwal, Eddie Calleja, Timur Rvachov, Neha Tadimeti, Roy Tal, Emine Küçükbenli

CoRR, March, 2026

2025

Multitask finetuning and acceleration of chemical pretrained models for small molecule drug property prediction.

Matthew Adrian, Yunsie Chung, Kevin Boyd, Saee Paliwal, Srimukh Prasad Veccham, Alan C. Cheng

CoRR, October, 2025

Rethinking Molecule Synthesizability with Chain-of-Reaction.

Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Saee Paliwal, Weili Nie, Arash Vahdat

CoRR, September, 2025

ToxBench: A Binding Affinity Prediction Benchmark with AB-FEP-Calculated Labels for Human Estrogen Receptor Alpha.

Meng Liu, Karl Leswing, Simon K. S. Chu, Farhad Ramezanghorbani, Griffin Young, Gabriel Marques, Prerna Das, Anjali Panikar, Esther Jamir, Mohammed Sulaiman Shamsudeen, K. Shawn Watts, Ananya Sen, Hari Priya Devannagari, Edward B. Miller, Muyun Lihan, Howook Hwang, Janet Paulsen, Xin Yu, Kyle Gion, Timur Rvachov, Emine Küçükbenli, Saee Gopal Paliwal

CoRR, July, 2025

Applications of Modular Co-Design for De Novo 3D Molecule Generation.

Danny Reidenbach, Filipp Nikitin, Olexandr Isayev, Saee Paliwal

CoRR, May, 2025

GenMol: A Drug Discovery Generalist with Discrete Diffusion.

Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Yuxing Peng, Saee Gopal Paliwal, Weili Nie, Arash Vahdat

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery.

Peter St. John, Dejun Lin, Polina Binder, Malcolm Greaves, Vega Shah, John St. John, Adrian Lange, Patrick D. Hsu, Rajesh Illango, Arvind Ramanathan, Anima Anandkumar, David H. Brookes, Akosua Busia, Abhishaike Mahajan, Stephen Malina, Neha Prasad, Sam Sinai, Lindsay Edwards, Thomas Gaudelet, Cristian Regep, Martin Steinegger, Burkhard Rost, Alexander Brace, Kyle Hippe, Luca Naef, Keisuke Kamata, George Armstrong, Kevin Boyd, Zhonglin Cao, Han-Yi Chou, Simon Chu, Allan dos Santos Costa, Sajad Darabi, Eric Dawson, Kieran Didi, Cong Fu, Mario Geiger, Michelle Gill, Darren Hsu, Gagan Kaushik, Maria Korshunova, Steven Kothen-Hill, Youhan Lee, Meng Liu, Micha Livne, Zachary McClure, Jonathan Mitchell, Alireza Moradzadeh, Ohad Mosafi, Youssef Nashed, Saee Paliwal, Yuxing Peng, Sara Rabhi, Farhad Ramezanghorbani, Danny Reidenbach, Camir Ricketts, Brian Roland, Kushal Shah, Tyler Shimko, Hassan Sirelkhatim, Savitha Srinivasan, Abraham C. Stern, Dorota Toczydlowska, Srimukh Prasad Veccham, Niccolò Alberto Elia Venanzi, Anton Vorontsov, Jared Wilber, Isabel Wilkinson, Wei Jing Wong, Eva Xue, Cory Ye, Xin Yu, Yang Zhang, Guoqing Zhou, Becca Zandstein, Christian Dallago, Bruno Trentini, Emine Küçükbenli, Timur Rvachov, Eddie Calleja, Johnny Israeli, Harry Clifford, Risto Haukioja, Nicholas Haemel, Kyle Tretina, Neha Tadimeti, Anthony B. Costa

CoRR, 2024

UKAN: Unbound Kolmogorov-Arnold Network Accompanied with Accelerated Library.

Alireza Moradzadeh, Lukasz Wawrzyniak, Miles Macklin, Saee Gopal Paliwal

CoRR, 2024

DualBind: A Dual-Loss Framework for Protein-Ligand Binding Affinity Prediction.

Meng Liu, Saee Gopal Paliwal

CoRR, 2024

LinkLogic: A New Method and Benchmark for Explainable Knowledge Graph Predictions.

Niraj Kumar Singh, Gustavo Padilha Polleti, Saee Paliwal, Rachel Hodos-Nkhereanye

CoRR, 2024

Molecule Generation with Fragment Retrieval Augmentation.

Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Saee Paliwal, Arash Vahdat, Weili Nie

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2022

Pseudo-Riemannian Embedding Models for Multi-Relational Graph Representations.

Saee Paliwal, Angus Brayne, Benedek Fabian, Maciej Wiatrak, Aaron Sim

Proceedings of the 4th Conference on Automated Knowledge Base Construction, 2022

2021

Directed Graph Embeddings in Pseudo-Riemannian Manifolds.

Aaron Sim, Maciej Wiatrak, Angus Brayne, Páidí Creed, Saee Paliwal

Proceedings of the 38th International Conference on Machine Learning, 2021

2017

Perceived control in bounded-rational decision-making.

Saee Paliwal, Frederike Petzschner, Ekaterina I. Lomakina, Klaas Enno Stephan

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2015

Inversion of hierarchical Bayesian models using Gaussian processes.

Ekaterina I. Lomakina, Saee Paliwal, Andreea Oliviana Diaconescu, Kay Henning Brodersen, Eduardo A. Aponte, Joachim M. Buhmann, Klaas E. Stephan

NeuroImage, 2015

2014

A Model-based Analysis of Impulsivity using a Slot-machine Gambling Paradigm.

Saee Paliwal, Frederike Petzschner, Anna Katharina Schmitz, Marc Tittgemeyer, Klaas Enno Stephan

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014