Rob Fergus

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 82

Top Venues

CoRR

ICML

ICLR

NIPS

Publications

Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders. CoRR (2024)
Shengbang Tong, Ellis Brown, Penghao Wu, Sanghyun Woo, Manoj Middepogu, Sai Charitha Akula, Jihan Yang, Shusheng Yang, Adithya Iyer, Xichen Pan, Austin Wang, Rob Fergus, Yann LeCun, Saining Xie
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs. CoRR (2024)
Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders. ICLR (2024)
Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Grathwohl
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. CoRR (2023)
Jake Bruce, Ankit Anand, Bogdan Mazoure, Rob Fergus
Learning About Progress From Experts. ICLR (2023)
Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Sadeep Jayasumana, Veeranjaneyulu Sadhanala, Wittawat Jitkrittum, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar
EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval. CoRR (2023)
Bogdan Mazoure, Jake Bruce, Doina Precup, Rob Fergus, Ankit Anand
Accelerating exploration and representation learning with offline pre-training. CoRR (2023)
Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Sussman Grathwohl
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. ICML (2023)
Theodore Sumers, Kenneth Marino, Arun Ahuja, Rob Fergus, Ishita Dasgupta
Distilling Internet-Scale Vision-Language Models into Embodied Agents. ICML (2023)
Ishita Dasgupta, Christine Kaeser-Chen, Kenneth Marino, Arun Ahuja, Sheila Babayan, Felix Hill, Rob Fergus
Collaborating with language models for embodied reasoning. CoRR (2023)
Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar
Teacher Guided Training: An Efficient Framework for Knowledge Transfer. ICLR (2023)
Arun Ahuja, Kavya Kopparapu, Rob Fergus, Ishita Dasgupta
Hierarchical reinforcement learning with natural language subgoals. CoRR (2023)
Ulyana Piterbarg, Lerrel Pinto, Rob Fergus
NetHack is Hard to Hack. NeurIPS (2023)
Ulyana Piterbarg, Lerrel Pinto, Rob Fergus
diff History for Long-Context Language Agents. CoRR (2023)
Theodore Sumers, Kenneth Marino, Arun Ahuja, Rob Fergus, Ishita Dasgupta
Distilling Internet-Scale Vision-Language Models into Embodied Agents. CoRR (2023)
Ulyana Piterbarg, Lerrel Pinto, Rob Fergus
NetHack is Hard to Hack. CoRR (2023)
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning. ICLR (2022)
Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar
Teacher Guided Training: An Efficient Framework for Knowledge Transfer. CoRR (2022)
Ronan Riochet, Mario Ynocente Castro, Mathieu Bernard, Adam Lerer, Rob Fergus, Véronique Izard, Emmanuel Dupoux
IntPhys 2019: A Benchmark for Visual Intuitive Physics Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 44 (9) (2022)
Manzil Zaheer, Kenneth Marino, Will Grathwohl, John Schultz, Wendy Shang, Sheila Babayan, Arun Ahuja, Ishita Dasgupta, Christine Kaeser-Chen, Rob Fergus
Learning to Navigate Wikipedia by Taking Random Walks. NeurIPS (2022)
Manzil Zaheer, Kenneth Marino, Will Grathwohl, John Schultz, Wendy Shang, Sheila Babayan, Arun Ahuja, Ishita Dasgupta, Christine Kaeser-Chen, Rob Fergus
Learning to Navigate Wikipedia by Taking Random Walks. CoRR (2022)
Roberta Raileanu, Max Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus
Automatic Data Augmentation for Generalization in Reinforcement Learning. NeurIPS (2021)
Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum
Offline Reinforcement Learning with Fisher Divergence Critic Regularization. ICML (2021)
Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. AAAI (2021)
Alexander Rives, Joshua Meier, Tom Sercu, Siddharth Goyal, Zeming Lin, Jason Liu, Demi Guo, Myle Ott, C. Lawrence Zitnick, Jerry Ma, Rob Fergus
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences. Proc. Natl. Acad. Sci. USA 118 (15) (2021)
Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne
Imitation by Predicting Observations. CoRR (2021)
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
Reinforcement Learning with Prototypical Representations. ICML (2021)
Ilya Kostrikov, Jonathan Tompson, Rob Fergus, Ofir Nachum
Offline Reinforcement Learning with Fisher Divergence Critic Regularization. CoRR (2021)
Roberta Raileanu, Rob Fergus
Decoupling Value and Policy for Generalization in Reinforcement Learning. CoRR (2021)
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
Reinforcement Learning with Prototypical Representations. CoRR (2021)
Denis Yarats, Ilya Kostrikov, Rob Fergus
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels. ICLR (2021)
Roberta Raileanu, Rob Fergus
Decoupling Value and Policy for Generalization in Reinforcement Learning. ICML (2021)
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning. CoRR (2021)
Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne
Imitation by Predicting Observations. ICML (2021)
Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives
Energy-based models for atomic-resolution protein conformations. CoRR (2020)
Roberta Raileanu, Max Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus
Automatic Data Augmentation for Generalization in Deep Reinforcement Learning. CoRR (2020)
Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives
Energy-based models for atomic-resolution protein conformations. ICLR (2020)
Roberta Raileanu, Max Goldstein, Arthur Szlam, Rob Fergus
Fast Adaptation via Policy-Dynamics Value Functions. CoRR (2020)
Roberta Raileanu, Max Goldstein, Arthur Szlam, Rob Fergus
Fast Adaptation to New Environments via Policy-Dynamics Value Functions. ICML (2020)
Kenneth Marino, Rob Fergus, Arthur Szlam, Abhinav Gupta
Empirically Verifying Hypotheses Using Reinforcement Learning. CoRR (2020)
Ilya Kostrikov, Denis Yarats, Rob Fergus
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels. CoRR (2020)
Ethan Perez, Siddharth Karamcheti, Rob Fergus, Jason Weston, Douwe Kiela, Kyunghyun Cho
Finding Generalizable Evidence by Learning to Convince Q&A Models. EMNLP/IJCNLP (1) (2019)
Ethan Perez, Siddharth Karamcheti, Rob Fergus, Jason Weston, Douwe Kiela, Kyunghyun Cho
Finding Generalizable Evidence by Learning to Convince Q&A Models. CoRR (2019)
Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. CoRR (2019)
Kenneth Marino, Abhinav Gupta, Rob Fergus, Arthur Szlam
Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies. ICLR (Poster) (2019)
William F. Whitney, Rob Fergus
Disentangling Video with Independent Prediction. CoRR (2019)
Emily Denton, Rob Fergus
Stochastic Video Generation with a Learned Prior. ICML (2018)
Emily Denton, Rob Fergus
Stochastic Video Generation with a Learned Prior. CoRR (2018)
Amy Zhang, Adam Lerer, Sainbayar Sukhbaatar, Rob Fergus, Arthur Szlam
Composable Planning with Attributes. CoRR (2018)
Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov, Gabriel Synnaeve, Arthur Szlam, Rob Fergus
Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. ICLR (Poster) (2018)
Sainbayar Sukhbaatar, Emily Denton, Arthur Szlam, Rob Fergus
Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning. CoRR (2018)
Ronan Riochet, Mario Ynocente Castro, Mathieu Bernard, Adam Lerer, Rob Fergus, Véronique Izard, Emmanuel Dupoux
IntPhys: A Framework and Benchmark for Visual Intuitive Physics Reasoning. CoRR (2018)
Roberta Raileanu, Emily Denton, Arthur Szlam, Rob Fergus
Modeling Others using Oneself in Multi-Agent Reinforcement Learning. CoRR (2018)
Amy Zhang, Sainbayar Sukhbaatar, Adam Lerer, Arthur Szlam, Rob Fergus
Composable Planning with Attributes. ICML (2018)
Roberta Raileanu, Emily Denton, Arthur Szlam, Rob Fergus
Modeling Others using Oneself in Multi-Agent Reinforcement Learning. ICML (2018)
Ishan Misra, Ross B. Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der Maaten
Learning by Asking Questions. CVPR (2018)
Sainbayar Sukhbaatar, Ilya Kostrikov, Arthur Szlam, Rob Fergus
Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. CoRR (2017)
Ishan Misra, Ross B. Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der Maaten
Learning by Asking Questions. CoRR (2017)
Adam Lerer, Sam Gross, Rob Fergus
Learning Physical Intuition of Block Towers by Example. ICML (2016)
Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri
Deep End2End Voxel2Voxel Prediction. CVPR Workshops (2016)
Emily L. Denton, Sam Gross, Rob Fergus
Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks. CoRR (2016)
Adam Lerer, Sam Gross, Rob Fergus
Learning Physical Intuition of Block Towers by Example. CoRR (2016)
Wojciech Zaremba, Tomás Mikolov, Armand Joulin, Rob Fergus
Learning Simple Algorithms from Examples. ICML (2016)
Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus
Learning Multiagent Communication with Backpropagation. NIPS (2016)
Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus
Learning Multiagent Communication with Backpropagation. CoRR (2016)
Kevin D. Tang, Manohar Paluri, Li Fei-Fei, Rob Fergus, Lubomir D. Bourdev
Improving Image Classification with Location Context. CoRR (2015)
Emily Denton, Jason Weston, Manohar Paluri, Lubomir D. Bourdev, Rob Fergus
User Conditional Hashtag Prediction for Images. KDD (2015)
Ning Zhang, Manohar Paluri, Yaniv Taigman, Rob Fergus, Lubomir D. Bourdev
Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues. CoRR (2015)
Yunchao Gong, Marcin Pawlowski, Fei Yang, Louis Brandy, Lubomir D. Bourdev, Rob Fergus
Web scale photo hash clustering on a single machine. CVPR (2015)
Li Wan, David Eigen, Rob Fergus
End-to-end integration of a Convolutional Network, Deformable Parts Model and non-maximum suppression. CVPR (2015)
Wojciech Zaremba, Tomás Mikolov, Armand Joulin, Rob Fergus
Learning Simple Algorithms from Examples. CoRR (2015)
Brenden M. Lake, Wojciech Zaremba, Rob Fergus, Todd M. Gureckis
Deep Neural Networks Predict Category Typicality Ratings for Images. CogSci (2015)
Ning Zhang, Manohar Paluri, Yaniv Taigman, Rob Fergus, Lubomir D. Bourdev
Beyond frontal faces: Improving Person Recognition using multiple cues. CVPR (2015)
Sainbayar Sukhbaatar, Rob Fergus
Learning from Noisy Labels with Deep Neural Networks. ICLR (Workshop) (2015)
Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, Rob Fergus
Weakly Supervised Memory Networks. CoRR (2015)
Emily L. Denton, Soumith Chintala, Arthur Szlam, Rob Fergus
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks. NIPS (2015)
Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri
Deep End2End Voxel2Voxel Prediction. CoRR (2015)
Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri
Learning Spatiotemporal Features with 3D Convolutional Networks. ICCV (2015)
Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, Rob Fergus
End-To-End Memory Networks. NIPS (2015)
David Eigen, Rob Fergus
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture. ICCV (2015)
Bolei Zhou, Yuandong Tian, Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus
Simple Baseline for Visual Question Answering. CoRR (2015)
Sainbayar Sukhbaatar, Arthur Szlam, Gabriel Synnaeve, Soumith Chintala, Rob Fergus
MazeBase: A Sandbox for Learning from Games. CoRR (2015)
Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri
C3D: Generic Features for Video Analysis. CoRR (2014)
Lubomir D. Bourdev, Fei Yang, Rob Fergus
Deep Poselets for Human Detection. CoRR (2014)
Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, Yann LeCun
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks. ICLR (2014)
David Eigen, Christian Puhrsch, Rob Fergus
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network. NIPS (2014)
Emily L. Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation. NIPS (2014)
Wojciech Zaremba, Karol Kurach, Rob Fergus
Learning to Discover Efficient Mathematical Identities. CoRR (2014)
Emily Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation. CoRR (2014)
Nathan Silberman, David A. Sontag, Rob Fergus
Instance Segmentation of Indoor Scenes Using a Coverage Loss. ECCV (1) (2014)
David Eigen, Christian Puhrsch, Rob Fergus
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network. CoRR (2014)
Li Wan, David Eigen, Rob Fergus
End-to-End Integration of a Convolutional Network, Deformable Parts Model and Non-Maximum Suppression. CoRR (2014)
Wojciech Zaremba, Karol Kurach, Rob Fergus
Learning to Discover Efficient Mathematical Identities. NIPS (2014)
David Eigen, Jason Tyler Rolfe, Rob Fergus, Yann LeCun
Understanding Deep Architectures using a Recursive Convolutional Network. ICLR (Workshop Poster) (2014)
David Eigen, Rob Fergus
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture. CoRR (2014)
Matthew D. Zeiler, Rob Fergus
Visualizing and Understanding Convolutional Networks. ECCV (1) (2014)
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, Rob Fergus
Intriguing properties of neural networks. ICLR (Poster) (2014)
Matthew D. Zeiler, Rob Fergus
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks ICLR (2013)
Matthew D. Zeiler, Rob Fergus
Visualizing and Understanding Convolutional Networks. CoRR (2013)
David Eigen, Dilip Krishnan, Rob Fergus
Restoring an Image Taken through a Window Covered with Dirt or Rain. ICCV (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Rob Fergus