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ORCIDAaron C. Courville
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- affiliation: Université de Montréal, Department of Computer Science
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2020 – today
- 2021
[i127]Michael Noukhovitch, Travis LaCroix, Angeliki Lazaridou, Aaron C. Courville:
Emergent Communication under Competition. CoRR abs/2101.10276 (2021)- [i126]Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron C. Courville, Sarath Chandar:
Continuous Coordination As a Realistic Scenario for Lifelong Learning. CoRR abs/2103.03216 (2021) - [i125]Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron C. Courville, Joshua B. Tenenbaum, Chuang Gan:
Learning Task Decomposition with Ordered Memory Policy Network. CoRR abs/2103.10972 (2021) - [i124]Sai Rajeswar, Cyril Ibrahim, Nitin Surya, Florian Golemo, David Vázquez, Aaron C. Courville, Pedro O. Pinheiro:
Touch-based Curiosity for Sparse-Reward Tasks. CoRR abs/2104.00442 (2021) - 2020
- [j14]Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, Yoshua Bengio:
Generative adversarial networks. Commun. ACM 63(11): 139-144 (2020) - [j13]Sai Rajeswar, Fahim Mannan, Florian Golemo, Jérôme Parent-Lévesque, David Vázquez, Derek Nowrouzezahrai, Aaron C. Courville:
Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images Using a View-Based Representation. Int. J. Comput. Vis. 128(10): 2478-2493 (2020) - [c97]Faruk Ahmed, Aaron C. Courville:
Detecting Semantic Anomalies. AAAI 2020: 3154-3162 - [c96]Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio:
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. AIED (2) 2020: 387-392 - [c95]Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville:
Stochastic Neural Network with Kronecker Flow. AISTATS 2020: 4184-4194 - [c94]Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky:
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. BMVC 2020 - [c93]Shawn Tan, Yikang Shen, Alessandro Sordoni, Aaron C. Courville, Timothy J. O'Donnell:
Recursive Top-Down Production for Sentence Generation with Latent Trees. EMNLP (Findings) 2020: 2291-2307 - [c92]Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville:
Supervised Seeded Iterated Learning for Interactive Language Learning. EMNLP (1) 2020: 3962-3970 - [c91]Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare:
On Bonus Based Exploration Methods In The Arcade Learning Environment. ICLR 2020 - [c90]Jae Hyun Lim, Aaron C. Courville, Christopher J. Pal, Chin-Wei Huang:
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation. ICML 2020: 6061-6071 - [c89]Yuchen Lu, Soumye Singhal, Florian Strub, Aaron C. Courville, Olivier Pietquin:
Countering Language Drift with Seeded Iterated Learning. ICML 2020: 6437-6447 - [c88]Pedro O. Pinheiro, Amjad Almahairi, Ryan Y. Benmalek, Florian Golemo, Aaron C. Courville:
Unsupervised Learning of Dense Visual Representations. NeurIPS 2020 - [i123]Chin-Wei Huang, Laurent Dinh, Aaron C. Courville:
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models. CoRR abs/2002.07101 (2020) - [i122]David Krueger, Ethan Caballero, Jörn-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Rémi Le Priol, Aaron C. Courville:
Out-of-Distribution Generalization via Risk Extrapolation (REx). CoRR abs/2003.00688 (2020) - [i121]Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville:
Countering Language Drift with Seeded Iterated Learning. CoRR abs/2003.12694 (2020) - [i120]Sai Rajeswar, Fahim Mannan, Florian Golemo, Jérôme Parent-Lévesque, David Vázquez, Derek Nowrouzezahrai, Aaron C. Courville:
Pix2Shape - Towards Unsupervised Learning of 3D Scenes from Images using a View-based Representation. CoRR abs/2003.14166 (2020) - [i119]Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio:
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. CoRR abs/2005.06616 (2020) - [i118]Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky:
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. CoRR abs/2005.08230 (2020) - [i117]Jae Hyun Lim, Aaron C. Courville, Christopher J. Pal, Chin-Wei Huang:
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation. CoRR abs/2006.05164 (2020) - [i116]Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky:
Generative Graph Perturbations for Scene Graph Prediction. CoRR abs/2007.05756 (2020) - [i115]Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman:
Data-Efficient Reinforcement Learning with Momentum Predictive Representations. CoRR abs/2007.05929 (2020) - [i114]Samuel Lavoie-Marchildon, Faruk Ahmed, Aaron C. Courville:
Integrating Categorical Semantics into Unsupervised Domain Translation. CoRR abs/2010.01262 (2020) - [i113]Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville:
Supervised Seeded Iterated Learning for Interactive Language Learning. CoRR abs/2010.02975 (2020) - [i112]Shawn Tan, Yikang Shen, Timothy J. O'Donnell, Alessandro Sordoni, Aaron C. Courville:
Recursive Top-Down Production for Sentence Generation with Latent Trees. CoRR abs/2010.04704 (2020) - [i111]Yanzhi Chen, Dinghuai Zhang, Michael U. Gutmann, Aaron C. Courville, Zhanxing Zhu:
Neural Approximate Sufficient Statistics for Implicit Models. CoRR abs/2010.10079 (2020) - [i110]Rithesh Kumar, Kundan Kumar, Vicki Anand, Yoshua Bengio, Aaron C. Courville:
NU-GAN: High resolution neural upsampling with GAN. CoRR abs/2010.11362 (2020) - [i109]Pedro O. Pinheiro, Amjad Almahairi, Ryan Y. Benmalek, Florian Golemo, Aaron C. Courville:
Unsupervised Learning of Dense Visual Representations. CoRR abs/2011.05499 (2020) - [i108]Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron C. Courville:
Explicitly Modeling Syntax in Language Model improves Generalization. CoRR abs/2011.07960 (2020) - [i107]Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. CoRR abs/2011.09468 (2020) - [i106]Yikang Shen, Yi Tay, Che Zheng, Dara Bahri, Donald Metzler, Aaron C. Courville:
StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language Modeling. CoRR abs/2012.00857 (2020) - [i105]Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron C. Courville:
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization. CoRR abs/2012.05942 (2020)
2010 – 2019
- 2019
- [c87]Catalina Cangea, Eugene Belilovsky, Aaron C. Courville:
VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. BMVC 2019: 280 - [c86]Kyle Kastner, João Felipe Santos, Yoshua Bengio, Aaron C. Courville:
Representation Mixing for TTS Synthesis. ICASSP 2019: 5906-5910 - [c85]Mikolaj Binkowski, R. Devon Hjelm, Aaron C. Courville:
Batch Weight for Domain Adaptation With Mass Shift. ICCV 2019: 1844-1853 - [c84]Lluís Castrejón, Nicolas Ballas, Aaron C. Courville:
Improved Conditional VRNNs for Video Prediction. ICCV 2019: 7607-7616 - [c83]Dzmitry Bahdanau, Shikhar Murty, Michael Noukhovitch, Thien Huu Nguyen, Harm de Vries, Aaron C. Courville:
Systematic Generalization: What Is Required and Can It Be Learned? ICLR (Poster) 2019 - [c82]Yikang Shen, Shawn Tan, Alessandro Sordoni, Aaron C. Courville:
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks. ICLR 2019 - [c81]Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron C. Courville:
Hierarchical Importance Weighted Autoencoders. ICML 2019: 2869-2878 - [c80]Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler, Min Lin, Fred A. Hamprecht, Yoshua Bengio, Aaron C. Courville:
On the Spectral Bias of Neural Networks. ICML 2019: 5301-5310 - [c79]Lucas Caccia, Herke van Hoof, Aaron C. Courville, Joelle Pineau:
Deep Generative Modeling of LiDAR Data. IROS 2019: 5034-5040 - [c78]Philip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Joelle Pineau, Satinder Singh, Aaron C. Courville:
No-Press Diplomacy: Modeling Multi-Agent Gameplay. NeurIPS 2019: 4476-4487 - [c77]Yikang Shen, Shawn Tan, Seyed Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron C. Courville:
Ordered Memory. NeurIPS 2019: 5038-5049 - [c76]Kundan Kumar, Rithesh Kumar, Thibault de Boissiere, Lucas Gestin, Wei Zhen Teoh, Jose Sotelo, Alexandre de Brébisson, Yoshua Bengio, Aaron C. Courville:
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis. NeurIPS 2019: 14881-14892 - [c75]Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron C. Courville:
Probability Distillation: A Caveat and Alternatives. UAI 2019: 1212-1221 - [i104]Catalina Cangea, Eugene Belilovsky, Pietro Liò, Aaron C. Courville:
VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. ViGIL@NeurIPS 2019 - [i103]Harm de Vries, Dzmitry Bahdanau, Shikhar Murty, Aaron C. Courville, Philippe Beaudoin:
CLOSURE: Assessing Systematic Generalization of CLEVR Models. ViGIL@NeurIPS 2019 - [i102]Rithesh Kumar, Anirudh Goyal, Aaron C. Courville, Yoshua Bengio:
Maximum Entropy Generators for Energy-Based Models. CoRR abs/1901.08508 (2019) - [i101]Cheng-Zhi Anna Huang, Tim Cooijmans, Adam Roberts, Aaron C. Courville, Douglas Eck:
Counterpoint by Convolution. CoRR abs/1903.07227 (2019) - [i100]Lluís Castrejón, Nicolas Ballas, Aaron C. Courville:
Improved Conditional VRNNs for Video Prediction. CoRR abs/1904.12165 (2019) - [i99]Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron C. Courville:
Hierarchical Importance Weighted Autoencoders. CoRR abs/1905.04866 (2019) - [i98]Mikolaj Binkowski, R. Devon Hjelm, Aaron C. Courville:
Batch weight for domain adaptation with mass shift. CoRR abs/1905.12760 (2019) - [i97]Chin-Wei Huang, Aaron C. Courville:
Note on the bias and variance of variational inference. CoRR abs/1906.03708 (2019) - [i96]Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville:
Stochastic Neural Network with Kronecker Flow. CoRR abs/1906.04282 (2019) - [i95]Shawn Tan, Yikang Shen, Chin-Wei Huang, Aaron C. Courville:
Investigating Biases in Textual Entailment Datasets. CoRR abs/1906.09635 (2019) - [i94]Jacob Leygonie, Jennifer She, Amjad Almahairi, Sai Rajeswar, Aaron C. Courville:
Adversarial Computation of Optimal Transport Maps. CoRR abs/1906.09691 (2019) - [i93]Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare:
Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment. CoRR abs/1908.02388 (2019) - [i92]Faruk Ahmed, Aaron C. Courville:
Detecting semantic anomalies. CoRR abs/1908.04388 (2019) - [i91]Catalina Cangea, Eugene Belilovsky, Pietro Liò, Aaron C. Courville:
VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. CoRR abs/1908.04950 (2019) - [i90]Philip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Satinder Singh, Joelle Pineau, Aaron C. Courville:
No Press Diplomacy: Modeling Multi-Agent Gameplay. CoRR abs/1909.02128 (2019) - [i89]Kundan Kumar, Rithesh Kumar, Thibault de Boissiere, Lucas Gestin, Wei Zhen Teoh, Jose Sotelo, Alexandre de Brébisson, Yoshua Bengio, Aaron C. Courville:
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis. CoRR abs/1910.06711 (2019) - [i88]Shawn Tan, Guillaume Androz, Ahmad Chamseddine, Pierre Fecteau, Aaron C. Courville, Yoshua Bengio, Joseph Paul Cohen:
Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery. CoRR abs/1910.09570 (2019) - [i87]Yikang Shen, Shawn Tan, Seyedarian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron C. Courville:
Ordered Memory. CoRR abs/1910.13466 (2019) - [i86]Sara Hooker, Aaron C. Courville, Yann N. Dauphin, Andrea Frome:
Selective Brain Damage: Measuring the Disparate Impact of Model Pruning. CoRR abs/1911.05248 (2019) - [i85]Dzmitry Bahdanau, Harm de Vries, Timothy J. O'Donnell, Shikhar Murty, Philippe Beaudoin, Yoshua Bengio, Aaron C. Courville:
CLOSURE: Assessing Systematic Generalization of CLEVR Models. CoRR abs/1912.05783 (2019) - 2018
- [c74]Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin, Aaron C. Courville:
FiLM: Visual Reasoning with a General Conditioning Layer. AAAI 2018: 3942-3951 - [c73]Yikang Shen, Zhouhan Lin, Athul Paul Jacob, Alessandro Sordoni, Aaron C. Courville, Yoshua Bengio:
Straight to the Tree: Constituency Parsing with Neural Syntactic Distance. ACL (1) 2018: 1171-1180 - [c72]Florian Golemo, Adrien Ali Taïga, Aaron C. Courville, Pierre-Yves Oudeyer:
Sim-to-Real Transfer with Neural-Augmented Robot Simulation. CoRL 2018: 817-828 - [c71]Florian Strub, Mathieu Seurin, Ethan Perez, Harm de Vries, Jérémie Mary, Philippe Preux, Aaron C. Courville, Olivier Pietquin:
Visual Reasoning with Multi-hop Feature Modulation. ECCV (5) 2018: 808-831 - [c70]Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville:
HoME: a Household Multimodal Environment. ICLR (Workshop) 2018 - [c69]Yikang Shen, Zhouhan Lin, Chin-Wei Huang, Aaron C. Courville:
Neural Language Modeling by Jointly Learning Syntax and Lexicon. ICLR (Poster) 2018 - [c68]Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni, Philip Bachman, Aaron C. Courville:
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data. ICML 2018: 195-204 - [c67]Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar, Sherjil Ozair, Yoshua Bengio, R. Devon Hjelm, Aaron C. Courville:
Mutual Information Neural Estimation. ICML 2018: 530-539 - [c66]Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron C. Courville:
Neural Autoregressive Flows. ICML 2018: 2083-2092 - [c65]Sandeep Subramanian, Sai Rajeswar, Alessandro Sordoni, Adam Trischler, Aaron C. Courville, Chris Pal:
Towards Text Generation with Adversarially Learned Neural Outlines. NeurIPS 2018: 7562-7574 - [c64]Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville:
Improving Explorability in Variational Inference with Annealed Variational Objectives. NeurIPS 2018: 9724-9734 - [i84]Ishmael Belghazi, Sai Rajeswar, Aristide Baratin, R. Devon Hjelm, Aaron C. Courville:
MINE: Mutual Information Neural Estimation. CoRR abs/1801.04062 (2018) - [i83]Mohamed Ishmael Belghazi, Sai Rajeswar, Olivier Mastropietro, Negar Rostamzadeh, Jovana Mitrovic, Aaron C. Courville:
Hierarchical Adversarially Learned Inference. CoRR abs/1802.01071 (2018) - [i82]Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni, Philip Bachman, Aaron C. Courville:
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data. CoRR abs/1802.10151 (2018) - [i81]Yikang Shen, Shawn Tan, Chin-Wei Huang, Aaron C. Courville:
Generating Contradictory, Neutral, and Entailing Sentences. CoRR abs/1803.02710 (2018) - [i80]Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron C. Courville:
Neural Autoregressive Flows. CoRR abs/1804.00779 (2018) - [i79]Yikang Shen, Zhouhan Lin, Athul Paul Jacob, Alessandro Sordoni, Aaron C. Courville, Yoshua Bengio:
Straight to the Tree: Constituency Parsing with Neural Syntactic Distance. CoRR abs/1806.04168 (2018) - [i78]Vikas Verma, Alex Lamb, Christopher Beckham, Aaron C. Courville, Ioannis Mitliagkas, Yoshua Bengio:
Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer. CoRR abs/1806.05236 (2018) - [i77]Amjad Almahairi, Kyle Kastner, Kyunghyun Cho, Aaron C. Courville:
Learning Distributed Representations from Reviews for Collaborative Filtering. CoRR abs/1806.06875 (2018) - [i76]Nasim Rahaman, Devansh Arpit, Aristide Baratin, Felix Draxler
, Min Lin, Fred A. Hamprecht, Yoshua Bengio, Aaron C. Courville:
On the Spectral Bias of Deep Neural Networks. CoRR abs/1806.08734 (2018) - [i75]Florian Strub, Mathieu Seurin, Ethan Perez, Harm de Vries, Jérémie Mary, Philippe Preux, Aaron C. Courville, Olivier Pietquin:
Visual Reasoning with Multi-hop Feature Modulation. CoRR abs/1808.04446 (2018) - [i74]Adrien Ali Taïga, Aaron C. Courville, Marc G. Bellemare:
Approximate Exploration through State Abstraction. CoRR abs/1808.09819 (2018) - [i73]Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville:
Improving Explorability in Variational Inference with Annealed Variational Objectives. CoRR abs/1809.01818 (2018) - [i72]Remi Tachet des Combes, Mohammad Pezeshki, Samira Shabanian, Aaron C. Courville, Yoshua Bengio:
On the Learning Dynamics of Deep Neural Networks. CoRR abs/1809.06848 (2018) - [i71]Yikang Shen, Shawn Tan, Alessandro Sordoni, Aaron C. Courville:
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks. CoRR abs/1810.09536 (2018) - [i70]Ankesh Anand, Eugene Belilovsky, Kyle Kastner, Hugo Larochelle, Aaron C. Courville:
Blindfold Baselines for Embodied QA. CoRR abs/1811.05013 (2018) - [i69]Kyle Kastner, João Felipe Santos, Yoshua Bengio, Aaron C. Courville:
Representation Mixing for TTS Synthesis. CoRR abs/1811.07240 (2018) - [i68]Kyle Kastner, Rithesh Kumar, Tim Cooijmans, Aaron C. Courville:
Harmonic Recomposition using Conditional Autoregressive Modeling. CoRR abs/1811.07426 (2018) - [i67]Johanna Hansen, Kyle Kastner, Aaron C. Courville, Gregory Dudek:
Planning in Dynamic Environments with Conditional Autoregressive Models. CoRR abs/1811.10097 (2018) - [i66]Dzmitry Bahdanau, Shikhar Murty, Michael Noukhovitch, Thien Huu Nguyen, Harm de Vries, Aaron C. Courville:
Systematic Generalization: What Is Required and Can It Be Learned? CoRR abs/1811.12889 (2018) - [i65]Lucas Caccia, Herke van Hoof, Aaron C. Courville, Joelle Pineau:
Deep Generative Modeling of LiDAR Data. CoRR abs/1812.01180 (2018) - 2017
- [j12]Anna Rohrbach, Atousa Torabi, Marcus Rohrbach, Niket Tandon, Christopher Joseph Pal, Hugo Larochelle, Aaron C. Courville, Bernt Schiele:
Movie Description. Int. J. Comput. Vis. 123(1): 94-120 (2017) - [j11]Mohammad Havaei, Axel Davy, David Warde-Farley, Antoine Biard, Aaron C. Courville, Yoshua Bengio, Chris Pal, Pierre-Marc Jodoin, Hugo Larochelle:
Brain tumor segmentation with Deep Neural Networks. Medical Image Anal. 35: 18-31 (2017) - [c63]Iulian Vlad Serban, Tim Klinger, Gerald Tesauro, Kartik Talamadupula, Bowen Zhou, Yoshua Bengio, Aaron C. Courville:
Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation. AAAI 2017: 3288-3294 - [c62]Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, Yoshua Bengio:
A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues. AAAI 2017: 3295-3301 - [c61]Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron C. Courville:
GuessWhat?! Visual Object Discovery through Multi-modal Dialogue. CVPR 2017: 4466-4475 - [c60]Tegan Maharaj, Nicolas Ballas, Anna Rohrbach, Aaron C. Courville, Christopher Joseph Pal:
A Dataset and Exploration of Models for Understanding Video Data through Fill-in-the-Blank Question-Answering. CVPR 2017: 7359-7368 - [c59]Iulian Vlad Serban, Alexander Ororbia, Joelle Pineau, Aaron C. Courville:
Piecewise Latent Variables for Neural Variational Text Processing. SPNLP@EMNLP 2017: 52-62 - [c58]Iulian Vlad Serban, Alexander G. Ororbia II, Joelle Pineau, Aaron C. Courville:
Piecewise Latent Variables for Neural Variational Text Processing. EMNLP 2017: 422-432 - [c57]Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron C. Courville, Yoshua Bengio:
An Actor-Critic Algorithm for Sequence Prediction. ICLR (Poster) 2017 - [c56]Tim Cooijmans, Nicolas Ballas, César Laurent, Çaglar Gülçehre, Aaron C. Courville:
Recurrent Batch Normalization. ICLR (Poster) 2017 - [c55]Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard H. Hovy, Aaron C. Courville:
Calibrating Energy-based Generative Adversarial Networks. ICLR (Poster) 2017 - [c54]Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville:
Adversarially Learned Inference. ICLR (Poster) 2017 - [c53]Ishaan Gulrajani, Kundan Kumar, Faruk Ahmed, Adrien Ali Taïga, Francesco Visin, David Vázquez, Aaron C. Courville:
PixelVAE: A Latent Variable Model for Natural Images. ICLR (Poster) 2017 - [c52]David Krueger, Nicolas Ballas, Stanislaw Jastrzebski, Devansh Arpit, Maxinder S. Kanwal, Tegan Maharaj, Emmanuel Bengio, Asja Fischer, Aaron C. Courville:
Deep Nets Don't Learn via Memorization. ICLR (Workshop) 2017 - [c51]David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron C. Courville, Christopher J. Pal:
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. ICLR (Poster) 2017 - [c50]Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Jose Sotelo, Aaron C. Courville, Yoshua Bengio:
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model. ICLR (Poster) 2017 - [c49]Mehdi Mirza, Aaron C. Courville, Yoshua Bengio:
Generalizable Features From Unsupervised Learning. ICLR (Workshop) 2017 - [c48]Jose Sotelo, Soroush Mehri, Kundan Kumar, João Felipe Santos, Kyle Kastner, Aaron C. Courville, Yoshua Bengio:
Char2Wav: End-to-End Speech Synthesis. ICLR (Workshop) 2017 - [c47]Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron C. Courville, Yoshua Bengio, Simon Lacoste-Julien:
A Closer Look at Memorization in Deep Networks. ICML 2017: 233-242 - [c46]Florian Strub, Harm de Vries, Jérémie Mary, Bilal Piot, Aaron C. Courville, Olivier Pietquin:
End-to-end optimization of goal-driven and visually grounded dialogue systems. IJCAI 2017: 2765-2771 - [c45]Cheng-Zhi Anna Huang, Tim Cooijmans, Adam Roberts, Aaron C. Courville, Douglas Eck:
Counterpoint by Convolution. ISMIR 2017: 211-218 - [c44]Alex Lamb, R. Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio:
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models. NIPS 2017: 5089-5098 - [c43]Ishaan Gulrajani, Faruk Ahmed, Martín Arjovsky, Vincent Dumoulin, Aaron C. Courville:
Improved Training of Wasserstein GANs. NIPS 2017: 5767-5777 - [c42]Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville:
Modulating early visual processing by language. NIPS 2017: 6594-6604 - [c41]Sandeep Subramanian, Sai Rajeswar, Francis Dutil, Chris Pal, Aaron C. Courville:
Adversarial Generation of Natural Language. Rep4NLP@ACL 2017: 241-251 - [i64]