Collaborative Filtering on a Family of Biological Targets. - Dumitru Erhan; Pierre-Jean L'Heureux; Shi Yi Yue; Yoshua Bengio (J. Chem. Inf. Model., 2006)

Aggregate features and ADABOOSTfor music classification. - James Bergstra; Norman Casagrande; Dumitru Erhan; Douglas Eck; Balázs Kégl (Mach. Learn., 2006)

An empirical evaluation of deep architectures on problems with many factors of variation. - Hugo Larochelle; Dumitru Erhan; Aaron C. Courville; James Bergstra; Yoshua Bengio (ICML, 2007)

Zero-data Learning of New Tasks. - Hugo Larochelle; Dumitru Erhan; Yoshua Bengio (AAAI, 2008)

The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training. - Dumitru Erhan; Pierre-Antoine Manzagol; Yoshua Bengio; Samy Bengio; Pascal Vincent (AISTATS, 2009)

Deep Learning using Robust Interdependent Codes. - Hugo Larochelle; Dumitru Erhan; Pascal Vincent (AISTATS, 2009)

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; et al. (CoRR, 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)

Why Does Unsupervised Pre-training Help Deep Learning? - Dumitru Erhan; Aaron C. Courville; Yoshua Bengio; Pascal Vincent (AISTATS, 2010)

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; et al. (AISTATS, 2011)

Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits. - Miroslav Dudík; Dumitru Erhan; John Langford 001; Lihong Li 001 (UAI, 2012)

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; et al. (ICONIP (3), 2013)

Deep Neural Networks for Object Detection. - Christian Szegedy; Alexander Toshev; Dumitru Erhan (NIPS, 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)

Scalable Object Detection Using Deep Neural Networks. - Dumitru Erhan; Christian Szegedy; Alexander Toshev; Dragomir Anguelov (CVPR, 2014)

Scalable, High-Quality Object Detection. - Christian Szegedy; Scott E. Reed; Dumitru Erhan; Dragomir Anguelov (CoRR, 2014)

Intriguing properties of neural networks. - Christian Szegedy; Wojciech Zaremba; Ilya Sutskever; Joan Bruna; Dumitru Erhan; Ian J. Goodfellow; Rob Fergus (ICLR (Poster), 2014)

Going deeper with convolutions. - Christian Szegedy; Wei Liu 015; Yangqing Jia; Pierre Sermanet; Scott E. Reed; Dragomir Anguelov; Dumitru Erhan; Vincent Vanhoucke; Andrew Rabinovich (CVPR, 2015)

Show and tell: A neural image caption generator. - Oriol Vinyals; Alexander Toshev; Samy Bengio; Dumitru Erhan (CVPR, 2015)

Doubly Robust Policy Evaluation and Optimization. - Miroslav Dudík; Dumitru Erhan; John Langford 001; Lihong Li 001 (CoRR, 2015)

Training Deep Neural Networks on Noisy Labels with Bootstrapping. - Scott E. Reed; Honglak Lee; Dragomir Anguelov; Christian Szegedy; Dumitru Erhan; Andrew Rabinovich (ICLR (Workshop), 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; et al. (Neural Networks, 2015)

SSD: Single Shot MultiBox Detector. - Wei Liu 015; Dragomir Anguelov; Dumitru Erhan; Christian Szegedy; Scott E. Reed; Cheng-Yang Fu; Alexander C. Berg (ECCV (1), 2016)

Domain Separation Networks. - Konstantinos Bousmalis; George Trigeorgis; Nathan Silberman; Dilip Krishnan; Dumitru Erhan (NIPS, 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; et al. (CoRR, 2016)

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks. - Konstantinos Bousmalis; Nathan Silberman; David Dohan; Dumitru Erhan; Dilip Krishnan (CVPR, 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)

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)

Stochastic Variational Video Prediction. - Mohammad Babaeizadeh; Chelsea Finn; Dumitru Erhan; Roy H. Campbell; Sergey Levine (ICLR (Poster), 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 (ICLR (Poster), 2018)

Hierarchical Long-term Video Prediction without Supervision. - Nevan Wichers; Ruben Villegas; Dumitru Erhan; Honglak Lee (ICML, 2018)

Evaluating Feature Importance Estimates. - Sara Hooker; Dumitru Erhan; Pieter-Jan Kindermans; Been Kim (CoRR, 2018)

A Benchmark for Interpretability Methods in Deep Neural Networks. - Sara Hooker; Dumitru Erhan; Pieter-Jan Kindermans; Been Kim (NeurIPS, 2019)

High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks. - Ruben Villegas; Arkanath Pathak; Harini Kannan; Dumitru Erhan; Quoc V. Le; Honglak Lee (NeurIPS, 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; et al. (CoRR, 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)

The (Un)reliability of Saliency Methods. - Pieter-Jan Kindermans; Sara Hooker; Julius Adebayo; Maximilian Alber; Kristof T. Schütt; Sven Dähne; Dumitru Erhan; Been Kim (Explainable AI, 2019)

SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving. - Zhenpei Yang; Yuning Chai; Dragomir Anguelov; Yin Zhou; Pei Sun; Dumitru Erhan; Sean Rafferty; Henrik Kretzschmar (CVPR, 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; et al. (ICLR, 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 (ICLR, 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)

FitVid: Overfitting in Pixel-Level Video Prediction. - Mohammad Babaeizadeh; Mohammad Taghi Saffar; Suraj Nair 003; Sergey Levine; Chelsea Finn; Dumitru Erhan (CoRR, 2021)

Information Prioritization through Empowerment in Visual Model-based RL. - Homanga Bharadhwaj; Mohammad Babaeizadeh; Dumitru Erhan; Sergey Levine (ICLR, 2022)

Phenaki: Variable Length Video Generation From Open Domain Textual Description. - Ruben Villegas; Mohammad Babaeizadeh; Pieter-Jan Kindermans; Hernan Moraldo; Han Zhang 010; Mohammad Taghi Saffar; Santiago Castro; Julius Kunze; Dumitru Erhan (CoRR, 2022)

Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions. - Ruben Villegas; Mohammad Babaeizadeh; Pieter-Jan Kindermans; Hernan Moraldo; Han Zhang 010; Mohammad Taghi Saffar; Santiago Castro; Julius Kunze; Dumitru Erhan (ICLR, 2023)

StoryBench: A Multifaceted Benchmark for Continuous Story Visualization. - Emanuele Bugliarello; H. Hernan Moraldo; Ruben Villegas; Mohammad Babaeizadeh; Mohammad Taghi Saffar; Han Zhang 010; Dumitru Erhan; Vittorio Ferrari; Pieter-Jan Kindermans; Paul Voigtlaender (NeurIPS, 2023)