Bharath Ramsundar

According to our database, Bharath Ramsundar authored at least 29 papers between 2013 and 2024.

Collaborative distances:

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

2024

Open-Source Fermionic Neural Networks with Ionic Charge Initialization.

Shai Pranesh, Shang Zhu, Venkat Viswanathan, Bharath Ramsundar

CoRR, 2024

2023

Scientific discovery in the age of artificial intelligence.

Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik

Nat., 2023

Differentiable Chemical Physics by Geometric Deep Learning for Gradient-based Property Optimization of Mixtures.

Shang Zhu, Bharath Ramsundar, Emil Annevelink, Hongyi Lin, Adarsh Dave, Pin-Wen Guan, Kevin Gering, Venkatasubramanian Viswanathan

CoRR, 2023

Open Source Infrastructure for Differentiable Density Functional Theory.

Advika Vidhyadhiraja, Arun Pa Thiagarajan, Shang Zhu, Venkat Viswanathan, Bharath Ramsundar

CoRR, 2023

2022

ChemBERTa-2: Towards Chemical Foundation Models.

Walid Ahmad, Elana Simon, Seyone Chithrananda, Gabriel Grand, Bharath Ramsundar

CoRR, 2022

Score-Based Generative Models for Molecule Generation.

Dwaraknath Gnaneshwar, Bharath Ramsundar, Dhairya Gandhi, Rachel C. Kurchin, Venkatasubramanian Viswanathan

CoRR, 2022

FastFlows: Flow-Based Models for Molecular Graph Generation.

Nathan C. Frey, Vijay Gadepally, Bharath Ramsundar

CoRR, 2022

2021

Bringing Atomistic Deep Learning to Prime Time.

Nathan C. Frey, Siddharth Samsi, Bharath Ramsundar, Connor W. Coley, Vijay Gadepally

CoRR, 2021

Differentiable Physics: A Position Piece.

Bharath Ramsundar, Dilip Krishnamurthy, Venkatasubramanian Viswanathan

CoRR, 2021

2020

AMPL: A Data-Driven Modeling Pipeline for Drug Discovery.

Amanda J. Minnich, Kevin McLoughlin, Margaret Tse, Jason Deng, Andrew Weber, Neha Murad, Benjamin D. Madej, Bharath Ramsundar, Tom Rush, Stacie Calad-Thomson, Jim Brase, Jonathan E. Allen

J. Chem. Inf. Model., 2020

ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction.

Seyone Chithrananda, Gabriel Grand, Bharath Ramsundar

CoRR, 2020

2019

From Data Science to Production ML: Introducing USENIX OpML.

Nisha Talagala, Bharath Ramsundar, Swaminathan Sundararaman

login Usenix Mag., 2019

Secure Computation in Decentralized Data Markets.

Fattaneh Bayatbabolghani, Bharath Ramsundar

CoRR, 2019

2018

Molecular machine learning with DeepChem.

Bharath Ramsundar

PhD thesis, 2018

Solving the RNA design problem with reinforcement learning.

Peter K. Eastman, Jade Shi, Bharath Ramsundar, Vijay S. Pande

PLoS Comput. Biol., 2018

Tokenized Data Markets.

Bharath Ramsundar, Roger Chen, Alok Vasudev, Rob Robbins, Artur Gorokh

CoRR, 2018

Spatial Graph Convolutions for Drug Discovery.

Evan N. Feinberg, Debnil Sur, Brooke E. Husic, Doris Mai, Yang Li, Jianyi Yang, Bharath Ramsundar, Vijay S. Pande

CoRR, 2018

2017

Is Multitask Deep Learning Practical for Pharma?

Bharath Ramsundar, Bowen Liu, Zhenqin Wu, Andreas Verras, Matthew Tudor, Robert P. Sheridan, Vijay S. Pande

J. Chem. Inf. Model., August, 2017

MoleculeNet: A Benchmark for Molecular Machine Learning.

Zhenqin Wu, Bharath Ramsundar, Evan N. Feinberg, Joseph Gomes, Caleb Geniesse, Aneesh S. Pappu, Karl Leswing, Vijay S. Pande

CoRR, 2017

Retrosynthetic reaction prediction using neural sequence-to-sequence models.

Bowen Liu, Bharath Ramsundar, Prasad Kawthekar, Jade Shi, Joseph Gomes, Quang Luu Nguyen, Stephen Ho, Jack Sloane, Paul Wender, Vijay S. Pande

CoRR, 2017

Atomic Convolutional Networks for Predicting Protein-Ligand Binding Affinity.

Joseph Gomes, Bharath Ramsundar, Evan N. Feinberg, Vijay S. Pande

CoRR, 2017

2016

Computational Modeling of β-Secretase 1 (BACE-1) Inhibitors Using Ligand Based Approaches.

Govindan Subramanian, Bharath Ramsundar, Vijay S. Pande, Rajiah Aldrin Denny

J. Chem. Inf. Model., 2016

Learning Protein Dynamics with Metastable Switching Systems.

Bharath Ramsundar, Vijay S. Pande

CoRR, 2016

Low Data Drug Discovery with One-shot Learning.

Han Altae-Tran, Bharath Ramsundar, Aneesh S. Pappu, Vijay S. Pande

CoRR, 2016

2015

Massively Multitask Networks for Drug Discovery.

Bharath Ramsundar, Steven Kearnes, Patrick Riley, Dale Webster, David E. Konerding, Vijay S. Pande

CoRR, 2015

2014

Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models.

Robert McGibbon, Bharath Ramsundar, Mohammad Sultan, Gert Kiss, Vijay S. Pande

Proceedings of the 31th International Conference on Machine Learning, 2014

NVMKV: A Scalable and Lightweight Flash Aware Key-Value Store.

Leonardo Mármol, Swaminathan Sundararaman, Nisha Talagala, Raju Rangaswami, Sushma Devendrappa, Bharath Ramsundar, Sriram Ganesan

Proceedings of the 6th USENIX Workshop on Hot Topics in Storage and File Systems, 2014

2013

The Extended Parameter Filter.

Yusuf Erol, Lei Li, Bharath Ramsundar, Stuart Russell

Proceedings of the 30th International Conference on Machine Learning, 2013

Dynamic Scaled Sampling for Deterministic Constraints.

Lei Li, Bharath Ramsundar, Stuart Russell

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013