Rob Fergus
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
50
Venues
9
Active years
2004–2025
Best venue rank
A*
Where they publish
Papers
50 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Efficient Exploration and Discriminative World Model Learning with an Object-Centric Abstraction. | Anthony GX-Chen, Kenneth Marino, Rob Fergus |
| 2025 | ICLR | BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games. | Davide Paglieri, Bartlomiej Cupial, Samuel Coward, Ulyana Piterbarg, Maciej Wolczyk, Akbir Khan, Eduardo Pignatelli, Lukasz Kucinski, Lerrel Pinto, Rob Fergus, Jakob Nicolaus Foerster, Jack Parker-Holder, Tim Rocktschel |
| 2025 | ICLR | Training Language Models on Synthetic Edit Sequences Improves Code Synthesis. | Ulyana Piterbarg, Lerrel Pinto, Rob Fergus |
| 2024 | ICLR | Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders. | Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum |
| 2024 | ICML | USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval. | Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Wittawat Jitkrittum, Veeranjaneyulu Sadhanala, Sadeep Jayasumana, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar |
| 2024 | ICML | A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks. | Nicholas Monath, Will Sussman Grathwohl, Michael Boratko, Rob Fergus, Andrew McCallum, Manzil Zaheer |
| 2024 | ICML | diff History for Neural Language Agents. | Ulyana Piterbarg, Lerrel Pinto, Rob Fergus |
| 2023 | ICLR | Learning About Progress From Experts. | Jake Bruce, Ankit Anand, Bogdan Mazoure, Rob Fergus |
| 2023 | ICLR | Teacher Guided Training: An Efficient Framework for Knowledge Transfer. | Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar |
| 2023 | ICML | Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. | Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Sussman Grathwohl |
| 2023 | ICML | Distilling Internet-Scale Vision-Language Models into Embodied Agents. | Theodore R. Sumers, Kenneth Marino, Arun Ahuja, Rob Fergus, Ishita Dasgupta |
| 2022 | ICLR | Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning. | Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto |
| 2021 | AAAI | Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. | Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus |
| 2021 | ICLR | Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels. | Denis Yarats, Ilya Kostrikov, Rob Fergus |
| 2021 | ICML | Imitation by Predicting Observations. | Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne |
| 2021 | ICML | Offline Reinforcement Learning with Fisher Divergence Critic Regularization. | Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum |
| 2021 | ICML | Decoupling Value and Policy for Generalization in Reinforcement Learning. | Roberta Raileanu, Rob Fergus |
| 2021 | ICML | Reinforcement Learning with Prototypical Representations. | Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto |
| 2020 | ICLR | Energy-based models for atomic-resolution protein conformations. | Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives |
| 2020 | ICML | Fast Adaptation to New Environments via Policy-Dynamics Value Functions. | Roberta Raileanu, Maxwell Goldstein, Arthur Szlam, Rob Fergus |
| 2019 | EMNLP | Finding Generalizable Evidence by Learning to Convince Q&A Models. | Ethan Perez, Siddharth Karamcheti, Rob Fergus, Jason Weston, Douwe Kiela, Kyunghyun Cho |
| 2019 | ICLR | Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies. | Kenneth Marino, Abhinav Gupta, Rob Fergus, Arthur Szlam |
| 2018 | CVPR | Learning by Asking Questions. | Ishan Misra, Ross B. Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der Maaten |
| 2018 | ICLR | Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. | Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov, Gabriel Synnaeve, Arthur Szlam, Rob Fergus |
| 2018 | ICML | Stochastic Video Generation with a Learned Prior. | Emily Denton, Rob Fergus |
| 2018 | ICML | Modeling Others using Oneself in Multi-Agent Reinforcement Learning. | Roberta Raileanu, Emily Denton, Arthur Szlam, Rob Fergus |
| 2018 | ICML | Composable Planning with Attributes. | Amy Zhang, Sainbayar Sukhbaatar, Adam Lerer, Arthur Szlam, Rob Fergus |
| 2016 | CVPR | Deep End2End Voxel2Voxel Prediction. | Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri |
| 2016 | ICML | Learning Physical Intuition of Block Towers by Example. | Adam Lerer, Sam Gross, Rob Fergus |
| 2016 | ICML | Learning Simple Algorithms from Examples. | Wojciech Zaremba, Toms Mikolov, Armand Joulin, Rob Fergus |
| 2015 | CogSci | Deep Neural Networks Predict Category Typicality Ratings for Images. | Brenden M. Lake, Wojciech Zaremba, Rob Fergus, Todd M. Gureckis |
| 2015 | CVPR | Web scale photo hash clustering on a single machine. | Yunchao Gong, Marcin Pawlowski, Fei Yang, Louis Brandy, Lubomir D. Bourdev, Rob Fergus |
| 2015 | CVPR | End-to-end integration of a Convolutional Network, Deformable Parts Model and non-maximum suppression. | Li Wan, David Eigen, Rob Fergus |
| 2015 | CVPR | Beyond frontal faces: Improving Person Recognition using multiple cues. | Ning Zhang, Manohar Paluri, Yaniv Taigman, Rob Fergus, Lubomir D. Bourdev |
| 2015 | ICCV | Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture. | David Eigen, Rob Fergus |
| 2015 | ICCV | Learning Spatiotemporal Features with 3D Convolutional Networks. | Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri |
| 2015 | KDD | User Conditional Hashtag Prediction for Images. | Emily Denton, Jason Weston, Manohar Paluri, Lubomir D. Bourdev, Rob Fergus |
| 2014 | ECCV | Instance Segmentation of Indoor Scenes Using a Coverage Loss. | Nathan Silberman, David A. Sontag, Rob Fergus |
| 2014 | ECCV | Visualizing and Understanding Convolutional Networks. | Matthew D. Zeiler, Rob Fergus |
| 2013 | ICCV | Restoring an Image Taken through a Window Covered with Dirt or Rain. | David Eigen, Dilip Krishnan, Rob Fergus |
| 2013 | ICML | Regularization of Neural Networks using DropConnect. | Li Wan, Matthew D. Zeiler, Sixin Zhang, Yann LeCun, Rob Fergus |
| 2012 | CVPR | Nonparametric image parsing using adaptive neighbor sets. | David Eigen, Rob Fergus |
| 2012 | ECCV | Indoor Segmentation and Support Inference from RGBD Images. | Nathan Silberman, Derek Hoiem, Pushmeet Kohli, Rob Fergus |
| 2012 | ECCV | Multidimensional Spectral Hashing. | Yair Weiss, Rob Fergus, Antonio Torralba |
| 2011 | CVPR | Blind deconvolution using a normalized sparsity measure. | Dilip Krishnan, Terence Tay, Rob Fergus |
| 2011 | CVPR | Learning invariance through imitation. | Graham W. Taylor, Ian Spiro, Christoph Bregler, Rob Fergus |
| 2011 | ICCV | Adaptive deconvolutional networks for mid and high level feature learning. | Matthew D. Zeiler, Graham W. Taylor, Rob Fergus |
| 2010 | ECCV | Convolutional Learning of Spatio-temporal Features. | Graham W. Taylor, Rob Fergus, Yann LeCun, Christoph Bregler |
| 2009 | CVPR | Learning invariant features through topographic filter maps. | Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergus, Yann LeCun |
| 2004 | CVPR | Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories. | Li Fei-Fei, Rob Fergus, Pietro Perona |