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Decision Transformer: Reinforcement Learning via Sequence Modeling


Jun 02, 2021
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch

* First two authors contributed equally. Last two authors advised equally 

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JUMBO: Scalable Multi-task Bayesian Optimization using Offline Data


Jun 02, 2021
Kourosh Hakhamaneshi, Pieter Abbeel, Vladimir Stojanovic, Aditya Grover


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Pretrained Transformers as Universal Computation Engines


Mar 09, 2021
Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch


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Anytime Sampling for Autoregressive Models via Ordered Autoencoding


Feb 23, 2021
Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon

* Accepted by ICLR 2021 

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Reset-Free Lifelong Learning with Skill-Space Planning


Jan 01, 2021
Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch

* Website link: https://sites.google.com/berkeley.edu/reset-free-lifelong-learning 

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PiRank: Learning To Rank via Differentiable Sorting


Dec 12, 2020
Robin Swezey, Aditya Grover, Bruno Charron, Stefano Ermon


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Permutation Invariant Graph Generation via Score-Based Generative Modeling


Mar 02, 2020
Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon

* 14 pages, AISTATS 2020 

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Fair Generative Modeling via Weak Supervision


Oct 26, 2019
Aditya Grover, Kristy Choi, Rui Shu, Stefano Ermon

* First two authors contributed equally 

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Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting


Jun 23, 2019
Aditya Grover, Jiaming Song, Alekh Agarwal, Kenneth Tran, Ashish Kapoor, Eric Horvitz, Stefano Ermon


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AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows


May 30, 2019
Aditya Grover, Christopher Chute, Rui Shu, Zhangjie Cao, Stefano Ermon


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Stochastic Optimization of Sorting Networks via Continuous Relaxations


Mar 21, 2019
Aditya Grover, Eric Wang, Aaron Zweig, Stefano Ermon

* ICLR 2019 

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Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization


Dec 26, 2018
Aditya Grover, Stefano Ermon

* AISTATS 2019 

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Learning Controllable Fair Representations


Dec 11, 2018
Jiaming Song, Pratyusha Kalluri, Aditya Grover, Shengjia Zhao, Stefano Ermon


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Streamlining Variational Inference for Constraint Satisfaction Problems


Nov 24, 2018
Aditya Grover, Tudor Achim, Stefano Ermon

* NeurIPS 2018 

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Learning Policy Representations in Multiagent Systems


Jul 31, 2018
Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yura Burda, Harrison Edwards

* ICML 2018 

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Modeling Sparse Deviations for Compressed Sensing using Generative Models


Jul 31, 2018
Manik Dhar, Aditya Grover, Stefano Ermon

* ICML 2018 

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Graphite: Iterative Generative Modeling of Graphs


Jun 19, 2018
Aditya Grover, Aaron Zweig, Stefano Ermon


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Variational Rejection Sampling


Apr 05, 2018
Aditya Grover, Ramki Gummadi, Miguel Lazaro-Gredilla, Dale Schuurmans, Stefano Ermon

* AISTATS 2018 

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Best arm identification in multi-armed bandits with delayed feedback


Mar 29, 2018
Aditya Grover, Todor Markov, Peter Attia, Norman Jin, Nicholas Perkins, Bryan Cheong, Michael Chen, Zi Yang, Stephen Harris, William Chueh, Stefano Ermon

* AISTATS 2018 

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Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models


Jan 03, 2018
Aditya Grover, Manik Dhar, Stefano Ermon

* AAAI 2018 

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Boosted Generative Models


Dec 22, 2017
Aditya Grover, Stefano Ermon

* AAAI 2018 

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node2vec: Scalable Feature Learning for Networks


Jul 03, 2016
Aditya Grover, Jure Leskovec

* In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016 

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Contextual Symmetries in Probabilistic Graphical Models


Jun 30, 2016
Ankit Anand, Aditya Grover, Mausam, Parag Singla

* IJCAI, 2016 
* 9 Pages, 4 figures 

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