Dumitru Erhan

61 papers A* 15A 5Journal 32Unranked 8
YearRankTypeTitle / Venue / Authors
2023 A* conf
Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions.
ICLR
Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan
2023 A* conf
StoryBench: A Multifaceted Benchmark for Continuous Story Visualization.
NeurIPS
Emanuele Bugliarello, H. Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender
2023 J jnl
StoryBench: A Multifaceted Benchmark for Continuous Story Visualization.
CoRR
Emanuele Bugliarello, Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender
2022 J jnl
INFOrmation Prioritization through EmPOWERment in Visual Model-Based RL.
CoRR
Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan, Sergey Levine
2022 A* conf
Information Prioritization through Empowerment in Visual Model-based RL.
ICLR
Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan, Sergey Levine
2022 J jnl
Phenaki: Variable Length Video Generation From Open Domain Textual Description.
CoRR
Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan
2021 J jnl
FitVid: Overfitting in Pixel-Level Video Prediction.
CoRR
Mohammad Babaeizadeh, Mohammad Taghi Saffar, Suraj Nair, Sergey Levine, Chelsea Finn, Dumitru Erhan
2020 A* conf
Model Based Reinforcement Learning for Atari.
ICLR
Lukasz Kaiser, Mohammad Babaeizadeh, Piotr Milos, Blazej Osinski, Roy H. Campbell, Konrad Czechowski, Dumitru Erhan, Chelsea Finn, Piotr Kozakowski, Sergey Levine, Afroz Mohiuddin, Ryan Sepassi, George Tucker, Henryk Michalewski
2020 J jnl
Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning.
CoRR
Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan, Chelsea Finn, Sergey Levine, Dumitru Erhan
2020 A* conf
SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving.
CVPR
Zhenpei Yang, Yuning Chai, Dragomir Anguelov, Yin Zhou, Pei Sun, Dumitru Erhan, Sean Rafferty, Henrik Kretzschmar
2020 J jnl
SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving.
CoRR
Zhenpei Yang, Yuning Chai, Dragomir Anguelov, Yin Zhou, Pei Sun, Dumitru Erhan, Sean Rafferty, Henrik Kretzschmar
2020 A* conf
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation.
ICLR
Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma
2019 A* conf
A Benchmark for Interpretability Methods in Deep Neural Networks.
NeurIPS
Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim
2019 A* conf
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks.
NeurIPS
Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee
2019 J jnl
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks.
CoRR
Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee
2019 J jnl
Model-Based Reinforcement Learning for Atari.
CoRR
Lukasz Kaiser, Mohammad Babaeizadeh, Piotr Milos, Blazej Osinski, Roy H. Campbell, Konrad Czechowski, Dumitru Erhan, Chelsea Finn, Piotr Kozakowski, Sergey Levine, Ryan Sepassi, George Tucker, Henryk Michalewski
2019 — ch.
The (Un)reliability of Saliency Methods.
Explainable AI
Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim
2019 J jnl
VideoFlow: A Flow-Based Generative Model for Video.
CoRR
Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma
2018 J jnl
Evaluating Feature Importance Estimates.
CoRR
Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim
2018 A* conf
Hierarchical Long-term Video Prediction without Supervision.
ICML
Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee
2018 J jnl
Hierarchical Long-term Video Prediction without Supervision.
CoRR
Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee
2018 — conf
Learning how to explain neural networks: PatternNet and PatternAttribution.
ICLR (Poster)
Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller, Dumitru Erhan, Been Kim, Sven Dähne
2018 — conf
Stochastic Variational Video Prediction.
ICLR (Poster)
Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, Sergey Levine
2017 J jnl
Show and Tell: Lessons Learned from the 2015 MSCOCO Image Captioning Challenge.
IEEE Trans. Pattern Anal. Mach. Intell.
Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan
2017 J jnl
Stochastic Variational Video Prediction.
CoRR
Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, Sergey Levine
2017 J jnl
The (Un)reliability of saliency methods.
CoRR
Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim
2017 A* conf
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks.
CVPR
Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan
2016 — conf
Domain Separation Networks.
NIPS
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan
2016 J jnl
Domain Separation Networks.
CoRR
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan
2016 — conf
SSD: Single Shot MultiBox Detector.
ECCV (1)
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott E. Reed, Cheng-Yang Fu, Alexander C. Berg
2016 J jnl
Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge.
CoRR
Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan
2016 J jnl
Theano: A Python framework for fast computation of mathematical expressions.
CoRR
Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang
2016 J jnl
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks.
CoRR
Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan
2015 J jnl
Challenges in representation learning: A report on three machine learning contests.
Neural Networks
Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William Cukierski, Yichuan Tang, David Thaler, Dong-hyun Lee, Yingbo Zhou, Chetan Ramaiah, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2015 J jnl
Doubly Robust Policy Evaluation and Optimization.
CoRR
Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
2015 A* conf
Going deeper with convolutions.
CVPR
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich
2015 J jnl
SSD: Single Shot MultiBox Detector.
CoRR
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott E. Reed, Cheng-Yang Fu, Alexander C. Berg
2015 A* conf
Show and tell: A neural image caption generator.
CVPR
Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan
2015 — conf
Training Deep Neural Networks on Noisy Labels with Bootstrapping.
ICLR (Workshop)
Scott E. Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich
2014 J jnl
Going Deeper with Convolutions.
CoRR
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich
2014 — conf
Intriguing properties of neural networks.
ICLR (Poster)
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, Rob Fergus
2014 A* conf
Scalable Object Detection Using Deep Neural Networks.
CVPR
Dumitru Erhan, Christian Szegedy, Alexander Toshev, Dragomir Anguelov
2014 J jnl
Scalable, High-Quality Object Detection.
CoRR
Christian Szegedy, Scott E. Reed, Dumitru Erhan, Dragomir Anguelov
2014 J jnl
Show and Tell: A Neural Image Caption Generator.
CoRR
Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan
2013 — conf
Challenges in Representation Learning: A Report on Three Machine Learning Contests.
ICONIP (3)
Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William Cukierski, Yichuan Tang, David Thaler, Dong-hyun Lee, Yingbo Zhou, Chetan Ramaiah, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2013 J jnl
Challenges in Representation Learning: A report on three machine learning contests.
CoRR
Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William Cukierski, Yichuan Tang, David Thaler, Dong-hyun Lee, Yingbo Zhou, Chetan Ramaiah, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2013 — conf
Deep Neural Networks for Object Detection.
NIPS
Christian Szegedy, Alexander Toshev, Dumitru Erhan
2013 J jnl
Scalable Object Detection using Deep Neural Networks.
CoRR
Dumitru Erhan, Christian Szegedy, Alexander Toshev, Dragomir Anguelov
2013 J jnl
Using Web Co-occurrence Statistics for Improving Image Categorization.
CoRR
Samy Bengio, Jeffrey Dean, Dumitru Erhan, Eugene Ie, Quoc V. Le, Andrew Rabinovich, Jonathon Shlens, Yoram Singer
2012 J jnl
Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits
CoRR
Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
2012 A conf
Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits.
UAI
Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
2011 A conf
Deep Learners Benefit More from Out-of-Distribution Examples.
AISTATS
Yoshua Bengio, Frédéric Bastien, Arnaud Bergeron, Nicolas Boulanger-Lewandowski, Thomas M. Breuel, Youssouf Chherawala, Moustapha Cissé, Myriam Côté, Dumitru Erhan, Jeremy Eustache, Xavier Glorot, Xavier Muller, Sylvain Pannetier Lebeuf, Razvan Pascanu, Salah Rifai, François Savard, Guillaume Sicard
2010 J jnl
Deep Self-Taught Learning for Handwritten Character Recognition
CoRR
Frédéric Bastien, Yoshua Bengio, Arnaud Bergeron, Nicolas Boulanger-Lewandowski, Thomas M. Breuel, Youssouf Chherawala, Moustapha Cissé, Myriam Côté, Dumitru Erhan, Jeremy Eustache, Xavier Glorot, Xavier Muller, Sylvain Pannetier Lebeuf, Razvan Pascanu, Salah Rifai, François Savard, Guillaume Sicard
2010 J jnl
Why Does Unsupervised Pre-training Help Deep Learning?
J. Mach. Learn. Res.
Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio
2010 A conf
Why Does Unsupervised Pre-training Help Deep Learning?
AISTATS
Dumitru Erhan, Aaron C. Courville, Yoshua Bengio, Pascal Vincent
2009 A conf
Deep Learning using Robust Interdependent Codes.
AISTATS
Hugo Larochelle, Dumitru Erhan, Pascal Vincent
2009 A conf
The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training.
AISTATS
Dumitru Erhan, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, Pascal Vincent
2008 A* conf
Zero-data Learning of New Tasks.
AAAI
Hugo Larochelle, Dumitru Erhan, Yoshua Bengio
2007 A* conf
An empirical evaluation of deep architectures on problems with many factors of variation.
ICML
Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra, Yoshua Bengio
2006 J jnl
Aggregate features and ADABOOSTfor music classification.
Mach. Learn.
James Bergstra, Norman Casagrande, Dumitru Erhan, Douglas Eck, Balázs Kégl
2006 J jnl
Collaborative Filtering on a Family of Biological Targets.
J. Chem. Inf. Model.
Dumitru Erhan, Pierre-Jean L'Heureux, Shi Yi Yue, Yoshua Bengio