Dumitru Erhan

According to our database, Dumitru Erhan authored at least 46 papers between 2006 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

StoryBench: A Multifaceted Benchmark for Continuous Story Visualization.

Emanuele Bugliarello, H. Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions.

Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Phenaki: Variable Length Video Generation From Open Domain Textual Description.

Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan

CoRR, 2022

Information Prioritization through Empowerment in Visual Model-based RL.

Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan, Sergey Levine

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

FitVid: Overfitting in Pixel-Level Video Prediction.

Mohammad Babaeizadeh, Mohammad Taghi Saffar, Suraj Nair, Sergey Levine, Chelsea Finn, Dumitru Erhan

CoRR, 2021

2020

Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning.

Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan, Chelsea Finn, Sergey Levine, Dumitru Erhan

CoRR, 2020

VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation.

Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma

Proceedings of the 8th International Conference on Learning Representations, 2020

Model Based Reinforcement Learning for Atari.

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

Proceedings of the 8th International Conference on Learning Representations, 2020

SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving.

Zhenpei Yang, Yuning Chai, Dragomir Anguelov, Yin Zhou, Pei Sun, Dumitru Erhan, Sean Rafferty, Henrik Kretzschmar

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

The (Un)reliability of Saliency Methods.

Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim

Proceedings of the Explainable AI: Interpreting, 2019

VideoFlow: A Flow-Based Generative Model for Video.

Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma

CoRR, 2019

Model-Based Reinforcement Learning for Atari.

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

CoRR, 2019

High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks.

Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Benchmark for Interpretability Methods in Deep Neural Networks.

Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Evaluating Feature Importance Estimates.

Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim

CoRR, 2018

Hierarchical Long-term Video Prediction without Supervision.

Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee

Proceedings of the 35th International Conference on Machine Learning, 2018

Learning how to explain neural networks: PatternNet and PatternAttribution.

Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller, Dumitru Erhan, Been Kim, Sven Dähne

Proceedings of the 6th International Conference on Learning Representations, 2018

Stochastic Variational Video Prediction.

Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, Sergey Levine

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Show and Tell: Lessons Learned from the 2015 MSCOCO Image Captioning Challenge.

Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan

IEEE Trans. Pattern Anal. Mach. Intell., 2017

The (Un)reliability of saliency methods.

Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim

CoRR, 2017

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks.

Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Theano: A Python framework for fast computation of mathematical expressions.

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

CoRR, 2016

Domain Separation Networks.

Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

SSD: Single Shot MultiBox Detector.

Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott E. Reed, Cheng-Yang Fu, Alexander C. Berg

Proceedings of the Computer Vision - ECCV 2016, 2016

2015

Challenges in representation learning: A report on three machine learning contests.

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

Neural Networks, 2015

Training Deep Neural Networks on Noisy Labels with Bootstrapping.

Scott E. Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich

Proceedings of the 3rd International Conference on Learning Representations, 2015

Doubly Robust Policy Evaluation and Optimization.

Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li

CoRR, 2015

Show and tell: A neural image caption generator.

Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Going deeper with convolutions.

Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Intriguing properties of neural networks.

Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, Rob Fergus

Proceedings of the 2nd International Conference on Learning Representations, 2014

Scalable, High-Quality Object Detection.

Christian Szegedy, Scott E. Reed, Dumitru Erhan, Dragomir Anguelov

CoRR, 2014

Scalable Object Detection Using Deep Neural Networks.

Dumitru Erhan, Christian Szegedy, Alexander Toshev, Dragomir Anguelov

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013

Using Web Co-occurrence Statistics for Improving Image Categorization.

Samy Bengio, Jeffrey Dean, Dumitru Erhan, Eugene Ie, Quoc V. Le, Andrew Rabinovich, Jonathon Shlens, Yoram Singer

CoRR, 2013

Deep Neural Networks for Object Detection.

Christian Szegedy, Alexander Toshev, Dumitru Erhan

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Challenges in Representation Learning: A Report on Three Machine Learning Contests.

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

Proceedings of the Neural Information Processing - 20th International Conference, 2013

2012

Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits.

Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

2011

Deep Learners Benefit More from Out-of-Distribution Examples.

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

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

2010

Why Does Unsupervised Pre-training Help Deep Learning?

Dumitru Erhan, Aaron C. Courville, Yoshua Bengio, Pascal Vincent

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Why Does Unsupervised Pre-training Help Deep Learning?

Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio

J. Mach. Learn. Res., 2010

Deep Self-Taught Learning for Handwritten Character Recognition

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

CoRR, 2010

2009

Deep Learning using Robust Interdependent Codes.

Hugo Larochelle, Dumitru Erhan, Pascal Vincent

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training.

Dumitru Erhan, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, Pascal Vincent

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

2008

Zero-data Learning of New Tasks.

Hugo Larochelle, Dumitru Erhan, Yoshua Bengio

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007

An empirical evaluation of deep architectures on problems with many factors of variation.

Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra, Yoshua Bengio

Proceedings of the Machine Learning, 2007

2006

Aggregate features and ADABOOSTfor music classification.

James Bergstra, Norman Casagrande, Dumitru Erhan, Douglas Eck, Balázs Kégl

Mach. Learn., 2006

Collaborative Filtering on a Family of Biological Targets.

Dumitru Erhan, Pierre-Jean L'Heureux, Shi Yi Yue, Yoshua Bengio

J. Chem. Inf. Model., 2006