| node2vec: Scalable feature learning for networks A Grover, J Leskovec Proceedings of the 22nd ACM SIGKDD international conference on Knowledge …, 2016 | 10446 | 2016 |
| Decision transformer: Reinforcement learning via sequence modeling L Chen, K Lu, A Rajeswaran, K Lee, A Grover, M Laskin, P Abbeel, ... Advances in neural information processing systems 34, 15084-15097, 2021 | 699 | 2021 |
| Closed-loop optimization of fast-charging protocols for batteries with machine learning PM Attia*, A Grover*, N Jin, KA Severson, TM Markov, YH Liao, MH Chen, ... Nature 578 (7795), 397-402, 2020 | 521 | 2020 |
| Graphite: Iterative generative modeling of graphs A Grover, A Zweig, S Ermon Proceedings of the 36th International Conference on Machine Learning, 2434-2444, 2019 | 282 | 2019 |
| A deep hybrid model for weather forecasting A Grover, A Kapoor, E Horvitz Proceedings of the 21st ACM SIGKDD International Conference on Knowledge …, 2015 | 266 | 2015 |
| Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models A Grover, M Dhar, S Ermon AAAI Conference on Artificial Intelligence, 2018 | 197* | 2018 |
| Pretrained transformers as universal computation engines K Lu, A Grover, P Abbeel, I Mordatch AAAI Conference on Artificial Intelligence, 2022 | 193 | 2022 |
| Learning controllable fair representations J Song, P Kalluri, A Grover, S Zhao, S Ermon Proceedings of the 22nd International Conference on Artificial Intelligence …, 2019 | 159 | 2019 |
| Stochastic optimization of sorting networks via continuous relaxations A Grover, E Wang, A Zweig, S Ermon International Conference on Learning Representations, 2019 | 129 | 2019 |
| Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting A Grover, J Song, A Agarwal, K Tran, A Kapoor, E Horvitz, S Ermon Advances in Neural Information Processing Systems, 11056--11068, 2019 | 114 | 2019 |
| Learning policy representations in multiagent systems A Grover, M Al-Shedivat, JK Gupta, Y Burda, H Edwards Proceedings of the 35th International Conference on Machine Learning, 1802-1811, 2018 | 113 | 2018 |
| Neural joint source-channel coding K Choi, K Tatwawadi, A Grover, T Weissman, S Ermon Proceedings of the 36th International Conference on Machine Learning, 1182-1192, 2019 | 107* | 2019 |
| Permutation invariant graph generation via score-based generative modeling C Niu, Y Song, J Song, S Zhao, A Grover, S Ermon International Conference on Artificial Intelligence and Statistics, 4474-4484, 2020 | 96 | 2020 |
| Fair generative modeling via weak supervision K Choi, A Grover, T Singh, R Shu, S Ermon International Conference on Machine Learning, 1887-1898, 2020 | 95* | 2020 |
| Online decision transformer Q Zheng, A Zhang, A Grover International Conference on Machine Learning, 2022 | 88 | 2022 |
| Modeling sparse deviations for compressed sensing using generative models M Dhar, A Grover, S Ermon Proceedings of the 35th International Conference on Machine Learning, 1214-1223, 2018 | 65 | 2018 |
| AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows A Grover, C Chute, R Shu, Z Cao, S Ermon AAAI Conference on Artificial Intelligence, 2020 | 60 | 2020 |
| Uncertainty autoencoders: Learning compressed representations via variational information maximization A Grover, S Ermon Proceedings of the 22nd International Conference on Artificial Intelligence …, 2019 | 53 | 2019 |
| Best arm identification in multi-armed bandits with delayed feedback A Grover, T Markov, P Attia, N Jin, N Perkins, B Cheong, M Chen, Z Yang, ... Proceedings of the 21st International Conference on Artificial Intelligence …, 2018 | 52 | 2018 |
| Bayesian learning for rapid prediction of lithium-ion battery-cycling protocols B Jiang, WE Gent, F Mohr, S Das, MD Berliner, M Forsuelo, H Zhao, ... Joule 5 (12), 3187-3203, 2021 | 49 | 2021 |
