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MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling


Dec 17, 2021
Yusong Wu, Ethan Manilow, Yi Deng, Rigel Swavely, Kyle Kastner, Tim Cooijmans, Aaron Courville, Cheng-Zhi Anna Huang, Jesse Engel


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DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization


Dec 09, 2021
Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron Courville, George Tucker, Sergey Levine


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Multi-label Iterated Learning for Image Classification with Label Ambiguity


Nov 23, 2021
Sai Rajeswar, Pau Rodriguez, Soumye Singhal, David Vazquez, Aaron Courville


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Chunked Autoregressive GAN for Conditional Waveform Synthesis


Oct 19, 2021
Max Morrison, Rithesh Kumar, Kundan Kumar, Prem Seetharaman, Aaron Courville, Yoshua Bengio

* Under review as a conference paper at ICLR 2022 

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Unifying Likelihood-free Inference with Black-box Sequence Design and Beyond


Oct 06, 2021
Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron Courville


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On Bonus-Based Exploration Methods in the Arcade Learning Environment


Sep 22, 2021
Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron Courville, Marc G. Bellemare

* Published as a conference paper at ICLR 2020 
* Full version of arXiv:1908.02388 

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Deep Reinforcement Learning at the Edge of the Statistical Precipice


Aug 30, 2021
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron Courville, Marc G. Bellemare


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Pretraining Representations for Data-Efficient Reinforcement Learning


Jun 09, 2021
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, Devon Hjelm, Philip Bachman, Aaron Courville


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Can Subnetwork Structure be the Key to Out-of-Distribution Generalization?


Jun 05, 2021
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville

* Accepted to ICML2021 as long talk 

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A Variational Perspective on Diffusion-Based Generative Models and Score Matching


Jun 05, 2021
Chin-Wei Huang, Jae Hyun Lim, Aaron Courville


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Hierarchical Video Generation for Complex Data


Jun 04, 2021
Lluis Castrejon, Nicolas Ballas, Aaron Courville


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Understanding by Understanding Not: Modeling Negation in Language Models


May 07, 2021
Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, R Devon Hjelm, Alessandro Sordoni, Aaron Courville


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Iterated learning for emergent systematicity in VQA


May 03, 2021
Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron Courville

* Published as a conference paper at ICLR 2021. 9 pages main, 21 pages total including references and appendix 

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Touch-based Curiosity for Sparse-Reward Tasks


Apr 01, 2021
Sai Rajeswar, Cyril Ibrahim, Nitin Surya, Florian Golemo, David Vazquez, Aaron Courville, Pedro O. Pinheiro


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Learning Task Decomposition with Ordered Memory Policy Network


Mar 19, 2021
Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron Courville, Joshua B. Tenenbaum, Chuang Gan


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Continuous Coordination As a Realistic Scenario for Lifelong Learning


Mar 04, 2021
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville, Sarath Chandar


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Emergent Communication under Competition


Jan 25, 2021
Michael Noukhovitch, Travis LaCroix, Angeliki Lazaridou, Aaron Courville

* To be presented at AAMAS 2021 

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StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language Modeling


Dec 15, 2020
Yikang Shen, Yi Tay, Che Zheng, Dara Bahri, Donald Metzler, Aaron Courville


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Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization


Dec 10, 2020
Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron Courville


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Gradient Starvation: A Learning Proclivity in Neural Networks


Nov 23, 2020
Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron Courville, Doina Precup, Guillaume Lajoie


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Unsupervised Learning of Dense Visual Representations


Nov 11, 2020
Pedro O. Pinheiro, Amjad Almahairi, Ryan Y. Benmaleck, Florian Golemo, Aaron Courville


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NU-GAN: High resolution neural upsampling with GAN


Oct 22, 2020
Rithesh Kumar, Kundan Kumar, Vicki Anand, Yoshua Bengio, Aaron Courville


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Neural Approximate Sufficient Statistics for Implicit Models


Oct 20, 2020
Yanzhi Chen, Dinghuai Zhang, Michael Gutmann, Aaron Courville, Zhanxing Zhu


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Recursive Top-Down Production for Sentence Generation with Latent Trees


Oct 09, 2020
Shawn Tan, Yikang Shen, Timothy J. O'Donnell, Alessandro Sordoni, Aaron Courville


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Supervised Seeded Iterated Learning for Interactive Language Learning


Oct 06, 2020
Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron Courville


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Integrating Categorical Semantics into Unsupervised Domain Translation


Oct 03, 2020
Samuel Lavoie-Marchildon, Faruk Ahmed, Aaron Courville

* 21 pages. In submission to the International Conference on Learning Representation (ICLR) 2021 

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Data-Efficient Reinforcement Learning with Momentum Predictive Representations


Jul 12, 2020
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville, Philip Bachman

* The first two authors contributed equally to this work 

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Generative Graph Perturbations for Scene Graph Prediction


Jul 11, 2020
Boris Knyazev, Harm de Vries, Cătălina Cangea, Graham W. Taylor, Aaron Courville, Eugene Belilovsky

* https://oolworkshop.github.io/program/ool_21.html, ICML Workshop 2020 on "Object-Oriented Learning (OOL): Perception, Representation, and Reasoning" 

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AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation


Jun 09, 2020
Jae Hyun Lim, Aaron Courville, Christopher Pal, Chin-Wei Huang

* accepted in ICML 2020 

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