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ORCIDRob Fergus
Robert Fergus
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- affiliation: New York University, Courant Institute
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2020 – today
- 2024
[c81]Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum:
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders. ICLR 2024- [c80]Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Wittawat Jitkrittum, Veeranjaneyulu Sadhanala, Sadeep Jayasumana, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar:
USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval. ICML 2024 - [c79]Nicholas Monath, Will Sussman Grathwohl, Michael Boratko, Rob Fergus, Andrew McCallum, Manzil Zaheer:
A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks. ICML 2024 - [c78]Ulyana Piterbarg, Lerrel Pinto, Rob Fergus:
diff History for Neural Language Agents. ICML 2024 - [i53]Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum:
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders. CoRR abs/2405.03651 (2024) - [i52]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 abs/2406.16860 (2024) - 2023
- [c77]Jake Bruce, Ankit Anand, Bogdan Mazoure, Rob Fergus:
Learning About Progress From Experts. ICLR 2023 - [c76]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 - [c75]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: 8489-8510 - [c74]Theodore R. Sumers, Kenneth Marino, Arun Ahuja, Rob Fergus, Ishita Dasgupta:
Distilling Internet-Scale Vision-Language Models into Embodied Agents. ICML 2023: 32797-32818 - [c73]Ulyana Piterbarg, Lerrel Pinto, Rob Fergus:
NetHack is Hard to Hack. NeurIPS 2023 - [i51]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 abs/2301.12005 (2023) - [i50]Theodore R. Sumers, Kenneth Marino, Arun Ahuja, Rob Fergus, Ishita Dasgupta:
Distilling Internet-Scale Vision-Language Models into Embodied Agents. CoRR abs/2301.12507 (2023) - [i49]Ishita Dasgupta, Christine Kaeser-Chen, Kenneth Marino, Arun Ahuja, Sheila Babayan, Felix Hill, Rob Fergus:
Collaborating with language models for embodied reasoning. CoRR abs/2302.00763 (2023) - [i48]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 abs/2302.11552 (2023) - [i47]Bogdan Mazoure, Jake Bruce, Doina Precup, Rob Fergus, Ankit Anand:
Accelerating exploration and representation learning with offline pre-training. CoRR abs/2304.00046 (2023) - [i46]Ulyana Piterbarg, Lerrel Pinto, Rob Fergus:
NetHack is Hard to Hack. CoRR abs/2305.19240 (2023) - [i45]Arun Ahuja, Kavya Kopparapu, Rob Fergus, Ishita Dasgupta:
Hierarchical reinforcement learning with natural language subgoals. CoRR abs/2309.11564 (2023) - [i44]Ulyana Piterbarg, Lerrel Pinto, Rob Fergus:
diff History for Long-Context Language Agents. CoRR abs/2312.07540 (2023) - 2022
- [j10]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): 5016-5025 (2022) - [c72]Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto:
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning. ICLR 2022 - [c71]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 - [i43]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 abs/2208.06825 (2022) - [i42]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 abs/2211.00177 (2022) - 2021
- [j9]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): e2016239118 (2021) - [c70]Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus:
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. AAAI 2021: 10674-10681 - [c69]Denis Yarats, Ilya Kostrikov, Rob Fergus:
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels. ICLR 2021 - [c68]Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne:
Imitation by Predicting Observations. ICML 2021: 4665-4676 - [c67]Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum:
Offline Reinforcement Learning with Fisher Divergence Critic Regularization. ICML 2021: 5774-5783 - [c66]Roberta Raileanu, Rob Fergus:
Decoupling Value and Policy for Generalization in Reinforcement Learning. ICML 2021: 8787-8798 - [c65]Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto:
Reinforcement Learning with Prototypical Representations. ICML 2021: 11920-11931 - [c64]Roberta Raileanu, Maxwell Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus:
Automatic Data Augmentation for Generalization in Reinforcement Learning. NeurIPS 2021: 5402-5415 - [i41]Roberta Raileanu, Rob Fergus:
Decoupling Value and Policy for Generalization in Reinforcement Learning. CoRR abs/2102.10330 (2021) - [i40]Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto:
Reinforcement Learning with Prototypical Representations. CoRR abs/2102.11271 (2021) - [i39]Ilya Kostrikov, Jonathan Tompson, Rob Fergus, Ofir Nachum:
Offline Reinforcement Learning with Fisher Divergence Critic Regularization. CoRR abs/2103.08050 (2021) - [i38]Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne:
Imitation by Predicting Observations. CoRR abs/2107.03851 (2021) - [i37]Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto:
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning. CoRR abs/2107.09645 (2021) - 2020
- [c63]Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives:
Energy-based models for atomic-resolution protein conformations. ICLR 2020 - [c62]Roberta Raileanu, Maxwell Goldstein, Arthur Szlam, Rob Fergus:
Fast Adaptation to New Environments via Policy-Dynamics Value Functions. ICML 2020: 7920-7931 - [i36]Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives:
Energy-based models for atomic-resolution protein conformations. CoRR abs/2004.13167 (2020) - [i35]Ilya Kostrikov, Denis Yarats, Rob Fergus:
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels. CoRR abs/2004.13649 (2020) - [i34]Roberta Raileanu, Maxwell Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus:
Automatic Data Augmentation for Generalization in Deep Reinforcement Learning. CoRR abs/2006.12862 (2020) - [i33]Kenneth Marino, Rob Fergus, Arthur Szlam, Abhinav Gupta:
Empirically Verifying Hypotheses Using Reinforcement Learning. CoRR abs/2006.15762 (2020) - [i32]Roberta Raileanu, Maxwell Goldstein, Arthur Szlam, Rob Fergus:
Fast Adaptation via Policy-Dynamics Value Functions. CoRR abs/2007.02879 (2020)
2010 – 2019
- 2019
- [c61]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: 2402-2411 - [c60]Kenneth Marino, Abhinav Gupta, Rob Fergus, Arthur Szlam:
Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies. ICLR (Poster) 2019 - [i31]William F. Whitney, Rob Fergus:
Disentangling Video with Independent Prediction. CoRR abs/1901.05590 (2019) - [i30]Ethan Perez, Siddharth Karamcheti, Rob Fergus, Jason Weston, Douwe Kiela, Kyunghyun Cho:
Finding Generalizable Evidence by Learning to Convince Q&A Models. CoRR abs/1909.05863 (2019) - [i29]Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus:
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. CoRR abs/1910.01741 (2019) - 2018
- [c59]Ishan Misra, Ross B. Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der Maaten:
Learning by Asking Questions. CVPR 2018: 11-20 - [c58]Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov, Gabriel Synnaeve, Arthur Szlam, Rob Fergus:
Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. ICLR (Poster) 2018 - [c57]Emily Denton, Rob Fergus:
Stochastic Video Generation with a Learned Prior. ICML 2018: 1182-1191 - [c56]Roberta Raileanu, Emily Denton, Arthur Szlam, Rob Fergus:
Modeling Others using Oneself in Multi-Agent Reinforcement Learning. ICML 2018: 4254-4263 - [c55]Amy Zhang, Sainbayar Sukhbaatar, Adam Lerer, Arthur Szlam, Rob Fergus:
Composable Planning with Attributes. ICML 2018: 5837-5846 - [i28]Emily Denton, Rob Fergus:
Stochastic Video Generation with a Learned Prior. CoRR abs/1802.07687 (2018) - [i27]Roberta Raileanu, Emily Denton, Arthur Szlam, Rob Fergus:
Modeling Others using Oneself in Multi-Agent Reinforcement Learning. CoRR abs/1802.09640 (2018) - [i26]Amy Zhang, Adam Lerer, Sainbayar Sukhbaatar, Rob Fergus, Arthur Szlam:
Composable Planning with Attributes. CoRR abs/1803.00512 (2018) - [i25]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 abs/1803.07616 (2018) - [i24]Sainbayar Sukhbaatar, Emily Denton, Arthur Szlam, Rob Fergus:
Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning. CoRR abs/1811.09083 (2018) - 2017
- [e1]Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, Roman Garnett:
Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA. 2017 [contents] - [i23]Sainbayar Sukhbaatar, Ilya Kostrikov, Arthur Szlam, Rob Fergus:
Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. CoRR abs/1703.05407 (2017) - [i22]Ishan Misra, Ross B. Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der Maaten:
Learning by Asking Questions. CoRR abs/1712.01238 (2017) - 2016
- [c54]Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri:
Deep End2End Voxel2Voxel Prediction. CVPR Workshops 2016: 402-409 - [c53]Wojciech Zaremba, Tomás Mikolov, Armand Joulin, Rob Fergus:
Learning Simple Algorithms from Examples. ICML 2016: 421-429 - [c52]Adam Lerer, Sam Gross, Rob Fergus:
Learning Physical Intuition of Block Towers by Example. ICML 2016: 430-438 - [c51]Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus:
Learning Multiagent Communication with Backpropagation. NIPS 2016: 2244-2252 - [i21]Adam Lerer, Sam Gross, Rob Fergus:
Learning Physical Intuition of Block Towers by Example. CoRR abs/1603.01312 (2016) - [i20]Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus:
Learning Multiagent Communication with Backpropagation. CoRR abs/1605.07736 (2016) - [i19]Emily L. Denton, Sam Gross, Rob Fergus:
Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks. CoRR abs/1611.06430 (2016) - 2015
- [c50]Brenden M. Lake, Wojciech Zaremba, Rob Fergus, Todd M. Gureckis:
Deep Neural Networks Predict Category Typicality Ratings for Images. CogSci 2015 - [c49]Yunchao Gong, Marcin Pawlowski, Fei Yang, Louis Brandy, Lubomir D. Bourdev, Rob Fergus:
Web scale photo hash clustering on a single machine. CVPR 2015: 19-27 - [c48]Li Wan, David Eigen, Rob Fergus:
End-to-end integration of a Convolutional Network, Deformable Parts Model and non-maximum suppression. CVPR 2015: 851-859 - [c47]Ning Zhang, Manohar Paluri, Yaniv Taigman, Rob Fergus, Lubomir D. Bourdev:
Beyond frontal faces: Improving Person Recognition using multiple cues. CVPR 2015: 4804-4813 - [c46]Kevin D. Tang, Manohar Paluri, Li Fei-Fei, Robert Fergus, Lubomir D. Bourdev:
Improving Image Classification with Location Context. ICCV 2015: 1008-1016 - [c45]David Eigen, Rob Fergus:
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture. ICCV 2015: 2650-2658 - [c44]Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri:
Learning Spatiotemporal Features with 3D Convolutional Networks. ICCV 2015: 4489-4497 - [c43]Emily Denton, Jason Weston, Manohar Paluri, Lubomir D. Bourdev, Rob Fergus:
User Conditional Hashtag Prediction for Images. KDD 2015: 1731-1740 - [c42]Emily L. Denton, Soumith Chintala, Arthur Szlam, Rob Fergus:
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks. NIPS 2015: 1486-1494 - [c41]Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, Rob Fergus:
End-To-End Memory Networks. NIPS 2015: 2440-2448 - [c40]Sainbayar Sukhbaatar, Rob Fergus:
Learning from Noisy Labels with Deep Neural Networks. ICLR (Workshop) 2015 - [i18]Ning Zhang, Manohar Paluri, Yaniv Taigman, Rob Fergus, Lubomir D. Bourdev:
Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues. CoRR abs/1501.05703 (2015) - [i17]Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, Rob Fergus:
Weakly Supervised Memory Networks. CoRR abs/1503.08895 (2015) - [i16]Kevin D. Tang, Manohar Paluri, Li Fei-Fei, Rob Fergus, Lubomir D. Bourdev:
Improving Image Classification with Location Context. CoRR abs/1505.03873 (2015) - [i15]Emily L. Denton, Soumith Chintala, Arthur Szlam, Robert Fergus:
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks. CoRR abs/1506.05751 (2015) - [i14]Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri:
Deep End2End Voxel2Voxel Prediction. CoRR abs/1511.06681 (2015) - [i13]Wojciech Zaremba, Tomás Mikolov, Armand Joulin, Rob Fergus:
Learning Simple Algorithms from Examples. CoRR abs/1511.07275 (2015) - [i12]Sainbayar Sukhbaatar, Arthur Szlam, Gabriel Synnaeve, Soumith Chintala, Rob Fergus:
MazeBase: A Sandbox for Learning from Games. CoRR abs/1511.07401 (2015) - [i11]Bolei Zhou, Yuandong Tian, Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus:
Simple Baseline for Visual Question Answering. CoRR abs/1512.02167 (2015) - 2014
- [c39]Nathan Silberman, David A. Sontag, Rob Fergus:
Instance Segmentation of Indoor Scenes Using a Coverage Loss. ECCV (1) 2014: 616-631 - [c38]Matthew D. Zeiler, Rob Fergus:
Visualizing and Understanding Convolutional Networks. ECCV (1) 2014: 818-833 - [c37]Emily L. Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus:
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation. NIPS 2014: 1269-1277 - [c36]Wojciech Zaremba, Karol Kurach, Rob Fergus:
Learning to Discover Efficient Mathematical Identities. NIPS 2014: 1278-1286 - [c35]David Eigen, Christian Puhrsch, Rob Fergus:
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network. NIPS 2014: 2366-2374 - [c34]David Eigen, Jason Tyler Rolfe, Rob Fergus, Yann LeCun:
Understanding Deep Architectures using a Recursive Convolutional Network. ICLR (Workshop Poster) 2014 - [c33]Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, Yann LeCun:
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks. ICLR 2014 - [c32]Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, Rob Fergus:
Intriguing properties of neural networks. ICLR (Poster) 2014 - [i10]Emily Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus:
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation. CoRR abs/1404.0736 (2014) - [i9]Wojciech Zaremba, Karol Kurach, Rob Fergus:
Learning to Discover Efficient Mathematical Identities. CoRR abs/1406.1584 (2014) - [i8]David Eigen, Christian Puhrsch, Rob Fergus:
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network. CoRR abs/1406.2283 (2014) - [i7]Lubomir D. Bourdev, Fei Yang, Rob Fergus:
Deep Poselets for Human Detection. CoRR abs/1407.0717 (2014) - [i6]David Eigen, Rob Fergus:
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture. CoRR abs/1411.4734 (2014) - [i5]Li Wan, David Eigen, Rob Fergus:
End-to-End Integration of a Convolutional Network, Deformable Parts Model and Non-Maximum Suppression. CoRR abs/1411.5309 (2014) - [i4]Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri:
C3D: Generic Features for Video Analysis. CoRR abs/1412.0767 (2014) - 2013
- [c31]David Eigen, Dilip Krishnan, Rob Fergus:
Restoring an Image Taken through a Window Covered with Dirt or Rain. ICCV 2013: 633-640 - [c30]Li Wan, Matthew D. Zeiler, Sixin Zhang, Yann LeCun, Rob Fergus:
Regularization of Neural Networks using DropConnect. ICML (3) 2013: 1058-1066 - [c29]Matthew D. Zeiler, Rob Fergus:
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks. ICLR 2013 - [p1]Kristen Grauman, Rob Fergus:
Learning Binary Hash Codes for Large-Scale Image Search. Machine Learning for Computer Vision 2013: 49-87 - [i3]Matthew D. Zeiler, Rob Fergus:
Visualizing and Understanding Convolutional Networks. CoRR abs/1311.2901 (2013) - [i2]Dilip Krishnan, Joan Bruna, Rob Fergus:
Blind Deconvolution with Re-weighted Sparsity Promotion. CoRR abs/1311.4029 (2013) - 2012
- [c28]David Eigen, Rob Fergus:
Nonparametric image parsing using adaptive neighbor sets. CVPR 2012: 2799-2806 - [c27]Yair Weiss, Rob Fergus, Antonio Torralba:
Multidimensional Spectral Hashing. ECCV (5) 2012: 340-353 - [c26]Nathan Silberman, Derek Hoiem, Pushmeet Kohli, Rob Fergus:
Indoor Segmentation and Support Inference from RGBD Images. ECCV (5) 2012: 746-760 - [c25]Li Wan, Leo Zhu, Rob Fergus:
A Hybrid Neural Network-Latent Topic Model. AISTATS 2012: 1287-1294 - [i1]Matthew D. Zeiler, Rob Fergus:
Differentiable Pooling for Hierarchical Feature Learning. CoRR abs/1207.0151 (2012) - 2011
- [c24]Dilip Krishnan, Terence Tay, Rob Fergus:
Blind deconvolution using a normalized sparsity measure. CVPR 2011: 233-240 - [c23]Graham W. Taylor, Ian Spiro, Christoph Bregler, Rob Fergus:
Learning invariance through imitation. CVPR 2011: 2729-2736 - [c22]Matthew D. Zeiler, Graham W. Taylor, Rob Fergus:
Adaptive deconvolutional networks for mid and high level feature learning. ICCV 2011: 2018-2025 - [c21]Nathan Silberman, Rob Fergus:
Indoor scene segmentation using a structured light sensor. ICCV Workshops 2011: 601-608 - [c20]Matthew D. Zeiler, Graham W. Taylor, Leonid Sigal, Iain A. Matthews, Rob Fergus:
Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines. NIPS 2011: 1629-1637 - 2010
- [j8]Robert Fergus, Li Fei-Fei, Pietro Perona, Andrew Zisserman:
Learning Object Categories From Internet Image Searches. Proc. IEEE 98(8): 1453-1466 (2010) - [c19]Nathan Silberman, Kristy Ahrlich, Rob Fergus, Lakshminarayanan Subramanian:
Case for Automated Detection of Diabetic Retinopathy. AAAI Spring Symposium: Artificial Intelligence for Development 2010 - [c18]Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylor, Robert Fergus:
Deconvolutional networks. CVPR 2010: 2528-2535 - [c17]Graham W. Taylor, Rob Fergus, Yann LeCun, Christoph Bregler:
Convolutional Learning of Spatio-temporal Features. ECCV (6) 2010: 140-153 - [c16]Robert Fergus, Hector Bernal, Yair Weiss, Antonio Torralba:
Semantic Label Sharing for Learning with Many Categories. ECCV (1) 2010: 762-775 - [c15]Graham W. Taylor, Rob Fergus, George Williams, Ian Spiro, Christoph Bregler:
Pose-Sensitive Embedding by Nonlinear NCA Regression. NIPS 2010: 2280-2288
2000 – 2009
- 2009
- [j7]Dilip Krishnan, Rob Fergus:
Dark flash photography. ACM Trans. Graph. 28(3): 96 (2009) - [c14]