publications

see Google Scholar for the most up-to-date information.

recent preprints

  1. arXiv
    Leaving Reality to Imagination: Robust Classification via Generated Datasets
    Hritik Bansal, and Aditya Grover
    2023
  2. arXiv
    ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling
    Tung Nguyen, Jason Jewik, Hritik Bansal, Prakhar Sharma, and Aditya Grover
    arXiv preprint arXiv:2307.01909, 2023
  3. arXiv
    Decision Stacks: Flexible Reinforcment Learning Via Modular Generative Models
    Siyan Zhao, and Aditya Grover
    arXiv preprint arXiv:2306.06253, 2023
  1. arXiv
    Reliable Conditioning of Behavioral Cloning for Offline Reinforcement Learning
    Tung Nguyen, Qinqing Zheng, and Aditya Grover
    arXiv preprint arXiv:2210.05158, 2022

              journal and conference articles

              2023

              1. ICML
                ClimaX: A foundation model for weather and climate
                Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K Gupta, and Aditya Grover
                In International Conference on Machine Learning (ICML), 2023
              2. ICML
                Generative pretraining for black-box optimization
                Satvik Mehul Mashkaria, Siddarth Krishnamoorthy, and Aditya Grover
                In International Conference on Machine Learning (ICML), 2023
              3. ICML
                Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories
                Qinqing Zheng, Mikael Henaff, Brandon Amos, and Aditya Grover
                In International Conference on Machine Learning (ICML), 2023
              4. ICML
                Diffusion Models for Offline Black-Box Optimization
                Siddarth Krishnamoorthy, Satvik Mehul Mashkaria, and Aditya Grover
                In International Conference on Machine Learning (ICML), 2023
              5. ICLR
                Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL
                Baiting Zhu, Meihua Dang, and Aditya Grover
                In International Conference on Learning Representations (ICLR), 2023
              6. ICCV
                CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning
                Hritik Bansal, Nishad Singhi, Yu Yang, Fan Yin, Aditya Grover*, and Kai-Wei Chang*
                In International Conference on Computer Vision (ICCV), 2023

              2022

              1. TMLR
                Controllable Generative Modeling via Causal Reasoning
                Joey Bose, Ricardo Pio Monti, and Aditya Grover
                Transactions of Machine Learning Research (TMLR), 2022
              2. NeurIPS
                Masked Autoencoding for Scalable and Generalizable Decision Making
                Fangchen Liu, Hao Liu, Aditya Grover, and Pieter Abbeel
                In Advances in Neural Information Processing Systems (NeurIPS), 2022
              3. NeurIPS
                CyCLIP: Cyclic Contrastive Language-Image Pretraining
                Shashank Goel, Hritik Bansal, Sumit Bhatia, Ryan A Rossi, Vishwa Vinay, and Aditya Grover
                In Advances in Neural Information Processing Systems (NeurIPS), 2022
              4. ICML
                Transformer neural processes: Uncertainty-aware meta learning via sequence modeling
                Tung Nguyen, and Aditya Grover
                In International Conference on Machine Learning (ICML), 2022
              5. ICML
                Online decision transformer
                Qinqing Zheng, Amy Zhang, and Aditya Grover
                In International Conference on Machine Learning (ICML), 2022
              6. ICML
                Matching normalizing flows and probability paths on manifolds
                Heli Ben-Hamu, Samuel Cohen, Joey Bose, Brandon Amos, Aditya Grover, Maximilian Nickel, Ricky Chen, and Yaron Lipman
                In International Conference on Machine Learning (ICML), 2022
              7. ICLR
                It Takes Four to Tango: Multiagent Selfplay for Automatic Curriculum Generation
                Yuqing Du, Pieter Abbeel, and Aditya Grover
                In International Conference on Learning Representations (ICLR), 2022
              8. ICLR
                Frame averaging for invariant and equivariant network design
                Omri Puny, Matan Atzmon, Heli Ben-Hamu, Edward J Smith, Ishan Misra, Aditya Grover, and Yaron Lipman
                In International Conference on Learning Representations (ICLR), 2022
              9. AAAI
                Pretrained transformers as universal computation engines
                Kevin Lu, Aditya Grover, Pieter Abbeel, and Igor Mordatch
                In AAAI Conference on Artificial Intelligence, 2022

              2021

              1. NeurIPS
                Moser flow: Divergence-based generative modeling on manifolds
                Noam Rozen, Aditya Grover, Maximilian Nickel, and Yaron Lipman
                Advances in Neural Information Processing Systems (NeurIPS), 2021
              2. NeurIPS
                BCD nets: Scalable variational approaches for Bayesian causal discovery
                Chris Cundy, Aditya Grover, and Stefano Ermon
                Advances in Neural Information Processing Systems (NeurIPS), 2021
              3. NeurIPS
                Pirank: Scalable learning to rank via differentiable sorting
                Robin Swezey, Aditya Grover, Bruno Charron, and Stefano Ermon
                Advances in Neural Information Processing Systems (NeurIPS), 2021
              4. NeurIPS
                Decision transformer: Reinforcement learning via sequence modeling
                Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Misha Laskin, Pieter Abbeel, Aravind Srinivas, and Igor Mordatch
                Advances in Neural Information Processing Systems (NeurIPS), 2021
              5. Joule
                Bayesian learning for rapid prediction of lithium-ion battery-cycling protocols
                Benben Jiang, William E Gent, Fabian Mohr, Supratim Das, Marc D Berliner, Michael Forsuelo, Hongbo Zhao, Peter M Attia, Aditya Grover, Patrick K Herring, and  others
                Joule, 2021
              6. ICLR
                Anytime sampling for autoregressive models via ordered autoencoding
                Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, and Stefano Ermon
                In International Conference on Learning Representations (ICLR), 2021
              7. ICLR
                Reset-free lifelong learning with skill-space planning
                Kevin Lu, Aditya Grover, Pieter Abbeel, and Igor Mordatch
                In International Conference on Learning Representations (ICLR), 2021
              8. AISTATS
                Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits
                Wenshuo Guo, Kumar Krishna Agrawal, Aditya Grover, Vidya Muthukumar, and Ashwin Pananjady
                In International Conference on Artificial Intelligence and Statistics (AISTATS), 2021

              2020

              1. Nature
                Closed-loop optimization of extreme fast charging for batteries using machine learning
                Peter Attia, Aditya Grover, Norman Jin, Kristen Severson, Bryan Cheong, Jerry Liao, Michael H Chen, Nicholas Perkins, Zi Yang, Patrick Herring, Muratahan Aykol, Stephen Harris, Richard Braatz, Stefano Ermon, and William Chueh
                Nature, 2020
              2. ICML
                Fair Generative Modeling via Weak Supervision
                Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, and Stefano Ermon
                In International Conference on Machine Learning (ICML), 2020
              3. AISTATS
                Permutation Invariant Graph Generation via Score-Based Generative Modeling
                Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, and Stefano Ermon
                In International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
              4. AAAI
                AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows
                Aditya Grover, Christopher Chute, Rui Shu, Zhangjie Cao, and Stefano Ermon
                In AAAI Conference on Artificial Intelligence, 2020

              2019

              1. NeurIPS
                Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting
                Aditya Grover, Jiaming Song, Alekh Agarwal, Kenneth Tran, Ashish Kapoor, Eric Horvitz, and Stefano Ermon
                In Advances in Neural Information Processing Systems (NeurIPS), 2019
              2. ICML
                Graphite: Iterative generative modeling of graphs
                Aditya Grover, Aaron Zweig, and Stefano Ermon
                In International Conference on Machine Learning (ICML), 2019
              3. ICML
                Neural Joint Source-Channel Coding
                Kristy Choi, Kedar Tatwawadi, Aditya Grover, Tsachy Weissman, and Stefano Ermon
                In International Conference on Machine Learning (ICML), 2019
              4. ICLR
                Stochastic Optimization of Sorting Networks via Continuous Relaxations
                Aditya Grover, Eric Wang, Aaron Zweig, and Stefano Ermon
                In International Conference on Learning Representations (ICLR), 2019
              5. AISTATS
                Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization
                Aditya Grover, and Stefano Ermon
                In International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
              6. AISTATS
                Learning Controllable Fair Representations
                Jiaming Song, Pratyusha Kalluri, Aditya Grover, Shengjia Zhao, and Stefano Ermon
                In International Conference on Artificial Intelligence and Statistics (AISTATS), 2019

              2018

              1. NeurIPS
                Streamlining variational inference for constraint satisfaction problems
                Aditya Grover, Tudor Achim, and Stefano Ermon
                In Advances in Neural Information Processing Systems (NeurIPS), 2018
              2. ICML
                Learning Policy Representations in Multiagent Systems
                Aditya Grover, Maruan Al-Shedivat, Jayesh K Gupta, Yura Burda, and Harrison Edwards
                In International Conference on Machine Learning (ICML), 2018
              3. ICML
                Modeling sparse deviations for compressed sensing using generative models
                Manik Dhar, Aditya Grover, and Stefano Ermon
                In International Conference on Machine Learning (ICML), 2018
              4. AISTATS
                Best arm identification in multi-armed bandits with delayed feedback
                Aditya Grover, Todor Markov, Peter Attia, Norman Jin, Nicholas Perkins, Bryan Cheong, Michael Chen, Zi Yang, Stephen Harris, William Chueh, and Stefano Ermon
                In International Conference on Artificial Intelligence and Statistics (AISTATS), 2018
              5. AISTATS
                Variational Rejection Sampling
                Aditya Grover, Ramki Gummadi, Miguel Lazaro-Gredilla, Dale Schuurmans, and Stefano Ermon
                In International Conference on Artificial Intelligence and Statistics (AISTATS), 2018
              6. AAMAS
                Evaluating Generalization in Multiagent Systems using Agent-Interaction Graphs
                Aditya Grover, Maruan Al-Shedivat, Jayesh K Gupta, Yuri Burda, and Harrison Edwards
                In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018
              7. AAAI
                Boosted generative models
                Aditya Grover, and Stefano Ermon
                In AAAI Conference on Artificial Intelligence, 2018
              8. AAAI
                Flow-GAN: Combining maximum likelihood and adversarial learning in generative models
                Aditya Grover, Manik Dhar, and Stefano Ermon
                In AAAI Conference on Artificial Intelligence, 2018

              2016

              1. NeurIPS
                Variational Bayes on Monte Carlo Steroids
                Aditya Grover, and Stefano Ermon
                In Advances in Neural Information Processing Systems (NeurIPS), 2016
              2. KDD
                node2vec: Scalable Feature Learning for Networks
                Aditya Grover, and Jure Leskovec
                In International Conference on Knowledge Discovery and Data Mining (KDD), 2016
              3. IJCAI
                Contextual Symmetries in Probabilistic Graphical Models
                Ankit Anand, Aditya Grover,  Mausam, and Parag Singla
                In International Joint Conference on Artificial Intelligence (IJCAI), 2016

              2015

              1. KDD
                A deep hybrid model for weather forecasting
                Aditya Grover, Ashish Kapoor, and Eric Horvitz
                In International Conference on Knowledge Discovery and Data Mining (KDD), 2015
              2. IJCAI
                ASAP-UCT: abstraction of state-action pairs in UCT
                Ankit Anand, Aditya Grover,  Mausam, and Parag Singla
                In International Joint Conference on Artificial Intelligence (IJCAI), 2015