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2020 – today
- 2024
[c5]Danika Gupta, Bharath Ramsundar:
Poster: Ensemble Methods for ADR Prediction. CHASE 2024: 210-211- [i23]Shai Pranesh, Shang Zhu, Venkat Viswanathan, Bharath Ramsundar:
Open-Source Fermionic Neural Networks with Ionic Charge Initialization. CoRR abs/2401.10287 (2024) - [i22]Varun Madhavan, Amal S. Sebastian, Bharath Ramsundar, Venkatasubramanian Viswanathan:
Self-supervised Pretraining for Partial Differential Equations. CoRR abs/2407.06209 (2024) - [i21]V. Shreyas, Jose Siguenza, Karan Bania, Bharath Ramsundar:
Open-Source Molecular Processing Pipeline for Generating Molecules. CoRR abs/2408.06261 (2024) - [i20]Aaron Rock Menezes, Bharath Ramsundar:
Open Source Infrastructure for Automatic Cell Segmentation. CoRR abs/2409.08163 (2024) - 2023
- [j6]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:
Scientific discovery in the age of artificial intelligence. Nat. 620(7972): 47-60 (2023) - [i19]Advika Vidhyadhiraja, Arun Pa Thiagarajan, Shang Zhu, Venkat Viswanathan, Bharath Ramsundar:
Open Source Infrastructure for Differentiable Density Functional Theory. CoRR abs/2309.15985 (2023) - [i18]Shang Zhu, Bharath Ramsundar, Emil Annevelink, Hongyi Lin, Adarsh Dave, Pin-Wen Guan, Kevin Gering, Venkatasubramanian Viswanathan:
Differentiable Chemical Physics by Geometric Deep Learning for Gradient-based Property Optimization of Mixtures. CoRR abs/2310.03047 (2023) - 2022
- [i17]Nathan C. Frey, Vijay Gadepally, Bharath Ramsundar:
FastFlows: Flow-Based Models for Molecular Graph Generation. CoRR abs/2201.12419 (2022) - [i16]Dwaraknath Gnaneshwar, Bharath Ramsundar, Dhairya Gandhi, Rachel C. Kurchin, Venkatasubramanian Viswanathan:
Score-Based Generative Models for Molecule Generation. CoRR abs/2203.04698 (2022) - [i15]Walid Ahmad, Elana Simon, Seyone Chithrananda, Gabriel Grand, Bharath Ramsundar:
ChemBERTa-2: Towards Chemical Foundation Models. CoRR abs/2209.01712 (2022) - 2021
- [i14]Bharath Ramsundar, Dilip Krishnamurthy, Venkatasubramanian Viswanathan:
Differentiable Physics: A Position Piece. CoRR abs/2109.07573 (2021) - [i13]Nathan C. Frey, Siddharth Samsi, Bharath Ramsundar, Connor W. Coley, Vijay Gadepally:
Bringing Atomistic Deep Learning to Prime Time. CoRR abs/2112.04977 (2021) - 2020
- [j5]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:
AMPL: A Data-Driven Modeling Pipeline for Drug Discovery. J. Chem. Inf. Model. 60(4): 1955-1968 (2020) - [i12]Seyone Chithrananda, Gabriel Grand, Bharath Ramsundar:
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction. CoRR abs/2010.09885 (2020)
2010 – 2019
- 2019
- [j4]Nisha Talagala, Bharath Ramsundar, Swaminathan Sundararaman:
From Data Science to Production ML: Introducing USENIX OpML. login Usenix Mag. 44(1) (2019) - [e1]Bharath Ramsundar, Nisha Talagala:
2019 USENIX Conference on Operational Machine Learning, OpML 2019, Santa Clara, CA, USA, May 20, 2019. USENIX Association 2019 [contents] - [i11]Fattaneh Bayatbabolghani, Bharath Ramsundar:
Secure Computation in Decentralized Data Markets. CoRR abs/1907.01489 (2019) - [i10]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:
AMPL: A Data-Driven Modeling Pipeline for Drug Discovery. CoRR abs/1911.05211 (2019) - 2018
- [b1]Bharath Ramsundar:
Molecular machine learning with DeepChem. Stanford University, USA, 2018 - [j3]Peter K. Eastman, Jade Shi, Bharath Ramsundar, Vijay S. Pande:
Solving the RNA design problem with reinforcement learning. PLoS Comput. Biol. 14(6) (2018) - [i9]Evan N. Feinberg, Debnil Sur, Brooke E. Husic, Doris Mai, Yang Li, Jianyi Yang, Bharath Ramsundar, Vijay S. Pande:
Spatial Graph Convolutions for Drug Discovery. CoRR abs/1803.04465 (2018) - [i8]Bharath Ramsundar, Roger Chen, Alok Vasudev, Rob Robbins, Artur Gorokh:
Tokenized Data Markets. CoRR abs/1806.00139 (2018) - 2017
- [j2]Bharath Ramsundar, Bowen Liu, Zhenqin Wu, Andreas Verras, Matthew Tudor, Robert P. Sheridan, Vijay S. Pande:
Is Multitask Deep Learning Practical for Pharma? J. Chem. Inf. Model. 57(8): 2068-2076 (2017) - [i7]Zhenqin Wu, Bharath Ramsundar, Evan N. Feinberg, Joseph Gomes, Caleb Geniesse, Aneesh S. Pappu, Karl Leswing, Vijay S. Pande:
MoleculeNet: A Benchmark for Molecular Machine Learning. CoRR abs/1703.00564 (2017) - [i6]Joseph Gomes, Bharath Ramsundar, Evan N. Feinberg, Vijay S. Pande:
Atomic Convolutional Networks for Predicting Protein-Ligand Binding Affinity. CoRR abs/1703.10603 (2017) - [i5]Bowen Liu, Bharath Ramsundar, Prasad Kawthekar, Jade Shi, Joseph Gomes, Quang Luu Nguyen, Stephen Ho, Jack Sloane, Paul Wender, Vijay S. Pande:
Retrosynthetic reaction prediction using neural sequence-to-sequence models. CoRR abs/1706.01643 (2017) - 2016
- [j1]Govindan Subramanian, Bharath Ramsundar, Vijay S. Pande, Rajiah Aldrin Denny:
Computational Modeling of β-Secretase 1 (BACE-1) Inhibitors Using Ligand Based Approaches. J. Chem. Inf. Model. 56(10): 1936-1949 (2016) - [i4]Bharath Ramsundar, Vijay S. Pande:
Learning Protein Dynamics with Metastable Switching Systems. CoRR abs/1610.01642 (2016) - [i3]Han Altae-Tran, Bharath Ramsundar, Aneesh S. Pappu, Vijay S. Pande:
Low Data Drug Discovery with One-shot Learning. CoRR abs/1611.03199 (2016) - 2015
- [i2]Bharath Ramsundar, Steven Kearnes, Patrick Riley, Dale Webster, David E. Konerding, Vijay S. Pande:
Massively Multitask Networks for Drug Discovery. CoRR abs/1502.02072 (2015) - 2014
- [c4]Leonardo Mármol, Swaminathan Sundararaman, Nisha Talagala, Raju Rangaswami, Sushma Devendrappa, Bharath Ramsundar, Sriram Ganesan:
NVMKV: A Scalable and Lightweight Flash Aware Key-Value Store. HotStorage 2014 - [c3]Robert McGibbon, Bharath Ramsundar, Mohammad Sultan, Gert Kiss, Vijay S. Pande:
Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models. ICML 2014: 1197-1205 - 2013
- [c2]Lei Li, Bharath Ramsundar, Stuart Russell:
Dynamic Scaled Sampling for Deterministic Constraints. AISTATS 2013: 397-405 - [c1]Yusuf Erol, Lei Li, Bharath Ramsundar, Stuart Russell:
The Extended Parameter Filter. ICML (3) 2013: 1103-1111 - [i1]Yusuf Erol, Lei Li, Bharath Ramsundar, Stuart Russell:
The Extended Parameter Filter. CoRR abs/1305.1704 (2013)
Coauthor Index
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last updated on 2024-10-14 23:31 CEST by the dblp team
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