Dumitru Erhan

Publication Activity (10 Years)

Years Active: 2006-2023
Publications (10 Years): 32

Top Topics

Reinforcement Learning

Mathematical Expressions

Top Venues

Publications

Emanuele Bugliarello, H. Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender
StoryBench: A Multifaceted Benchmark for Continuous Story Visualization. NeurIPS (2023)
Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan
Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions. ICLR (2023)
Emanuele Bugliarello, Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender
StoryBench: A Multifaceted Benchmark for Continuous Story Visualization. CoRR (2023)
Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan, Sergey Levine
INFOrmation Prioritization through EmPOWERment in Visual Model-Based RL. CoRR (2022)
Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan, Sergey Levine
Information Prioritization through Empowerment in Visual Model-based RL. ICLR (2022)
Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan
Phenaki: Variable Length Video Generation From Open Domain Textual Description. CoRR (2022)
Mohammad Babaeizadeh, Mohammad Taghi Saffar, Suraj Nair, Sergey Levine, Chelsea Finn, Dumitru Erhan
FitVid: Overfitting in Pixel-Level Video Prediction. CoRR (2021)
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
Model Based Reinforcement Learning for Atari. ICLR (2020)
Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan, Chelsea Finn, Sergey Levine, Dumitru Erhan
Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning. CoRR (2020)
Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation. ICLR (2020)
Zhenpei Yang, Yuning Chai, Dragomir Anguelov, Yin Zhou, Pei Sun, Dumitru Erhan, Sean Rafferty, Henrik Kretzschmar
SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving. CoRR (2020)
Zhenpei Yang, Yuning Chai, Dragomir Anguelov, Yin Zhou, Pei Sun, Dumitru Erhan, Sean Rafferty, Henrik Kretzschmar
SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving. CVPR (2020)
Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks. NeurIPS (2019)
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
Model-Based Reinforcement Learning for Atari. CoRR (2019)
Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma
VideoFlow: A Flow-Based Generative Model for Video. CoRR (2019)
Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks. CoRR (2019)
Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim
A Benchmark for Interpretability Methods in Deep Neural Networks. NeurIPS (2019)
Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, Sergey Levine
Stochastic Variational Video Prediction. ICLR (Poster) (2018)
Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller, Dumitru Erhan, Been Kim, Sven Dähne
Learning how to explain neural networks: PatternNet and PatternAttribution. ICLR (Poster) (2018)
Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim
Evaluating Feature Importance Estimates. CoRR (2018)
Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee
Hierarchical Long-term Video Prediction without Supervision. ICML (2018)
Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee
Hierarchical Long-term Video Prediction without Supervision. CoRR (2018)
Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks. CVPR (2017)
Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim
The (Un)reliability of saliency methods. CoRR (2017)
Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan
Show and Tell: Lessons Learned from the 2015 MSCOCO Image Captioning Challenge. IEEE Trans. Pattern Anal. Mach. Intell. 39 (4) (2017)
Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, Sergey Levine
Stochastic Variational Video Prediction. CoRR (2017)
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan
Domain Separation Networks. NIPS (2016)
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan
Domain Separation Networks. CoRR (2016)
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott E. Reed, Cheng-Yang Fu, Alexander C. Berg
SSD: Single Shot MultiBox Detector. ECCV (1) (2016)
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
Theano: A Python framework for fast computation of mathematical expressions. CoRR (2016)
Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks. CoRR (2016)
Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan
Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge. CoRR (2016)
Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan
Show and tell: A neural image caption generator. CVPR (2015)
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, Zhang Chuang, Yoshua Bengio
Challenges in representation learning: A report on three machine learning contests. Neural Networks 64 (2015)
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott E. Reed, Cheng-Yang Fu, Alexander C. Berg
SSD: Single Shot MultiBox Detector. CoRR (2015)
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich
Going deeper with convolutions. CVPR (2015)
Scott E. Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich
Training Deep Neural Networks on Noisy Labels with Bootstrapping. ICLR (Workshop) (2015)
Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
Doubly Robust Policy Evaluation and Optimization. CoRR (2015)
Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan
Show and Tell: A Neural Image Caption Generator. CoRR (2014)
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich
Going Deeper with Convolutions. CoRR (2014)
Christian Szegedy, Scott E. Reed, Dumitru Erhan, Dragomir Anguelov
Scalable, High-Quality Object Detection. CoRR (2014)
Dumitru Erhan, Christian Szegedy, Alexander Toshev, Dragomir Anguelov
Scalable Object Detection Using Deep Neural Networks. CVPR (2014)
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, Rob Fergus
Intriguing properties of neural networks. ICLR (Poster) (2014)
Samy Bengio, Jeffrey Dean, Dumitru Erhan, Eugene Ie, Quoc V. Le, Andrew Rabinovich, Jonathon Shlens, Yoram Singer
Using Web Co-occurrence Statistics for Improving Image Categorization. CoRR (2013)
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
Challenges in Representation Learning: A report on three machine learning contests. CoRR (2013)
Christian Szegedy, Alexander Toshev, Dumitru Erhan
Deep Neural Networks for Object Detection. NIPS (2013)
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
Challenges in Representation Learning: A Report on Three Machine Learning Contests. ICONIP (3) (2013)
Dumitru Erhan, Christian Szegedy, Alexander Toshev, Dragomir Anguelov
Scalable Object Detection using Deep Neural Networks. CoRR (2013)
Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits. UAI (2012)
Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits CoRR (2012)
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
Deep Learners Benefit More from Out-of-Distribution Examples. AISTATS (2011)
Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio
Why Does Unsupervised Pre-training Help Deep Learning? J. Mach. Learn. Res. 11 (2010)
Dumitru Erhan, Aaron C. Courville, Yoshua Bengio, Pascal Vincent
Why Does Unsupervised Pre-training Help Deep Learning? AISTATS (2010)
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
Deep Self-Taught Learning for Handwritten Character Recognition CoRR (2010)
Hugo Larochelle, Dumitru Erhan, Pascal Vincent
Deep Learning using Robust Interdependent Codes. AISTATS (2009)
Dumitru Erhan, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, Pascal Vincent
The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training. AISTATS (2009)
Hugo Larochelle, Dumitru Erhan, Yoshua Bengio
Zero-data Learning of New Tasks. AAAI (2008)
Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra, Yoshua Bengio
An empirical evaluation of deep architectures on problems with many factors of variation. ICML (2007)
James Bergstra, Norman Casagrande, Dumitru Erhan, Douglas Eck, Balázs Kégl
Aggregate features and ADABOOSTfor music classification. Mach. Learn. 65 (2-3) (2006)
Dumitru Erhan, Pierre-Jean L'Heureux, Shi Yi Yue, Yoshua Bengio
Collaborative Filtering on a Family of Biological Targets. J. Chem. Inf. Model. 46 (2) (2006)