Rob Fergus
- Computer Vision and Pattern Recognition top 0.01%
- Advanced Image and Video Retrieval Techniques 21
- Image Retrieval and Classification Techniques 13
- Advanced Vision and Imaging 12
- Advanced Image Processing Techniques 7
- Multimodal Machine Learning Applications 6
- Media Technology top 0.02%
- Image Processing Techniques and Applications 10
- Artificial Intelligence top 0.1%
- Domain Adaptation and Few-Shot Learning 10
- Reinforcement Learning in Robotics 6
- Signal Processing top 0.5%
- Aerospace Engineering top 0.5%
- Co-authors
- Pietro PeronaLi Fei-FeiAntonio TorralbaWilliam T. FreemanDilip KrishnanMatthew D. ZeilerDavid EigenYair Weiss
- Journals
- ACM Transactions on Graphics (4 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (3 papers)Journal of Vision (1 paper)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Rob Fergus
61 papers receiving 21.4k citations
Hit Papers
Peers
Comparison fields: 5 of 199
- Computer Vision and Pattern Recognition 16.8k
- Media Technology 5.2k
- Artificial Intelligence 5.5k
- Signal Processing 815
- Aerospace Engineering 1.7k
Countries citing papers authored by Rob Fergus
This map shows the geographic impact of Rob Fergus's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Rob Fergus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rob Fergus more than expected).
Fields of papers citing papers by Rob Fergus
This network shows the impact of papers produced by Rob Fergus. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Rob Fergus. The network helps show where Rob Fergus may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Rob Fergus, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequencesbreakdown → | 2021 | 1429 |
| 2 | Offline Reinforcement Learning with Fisher Divergence Critic Regularization | 2021 | 15 |
| 3 | Automatic Data Augmentation for Generalization in Reinforcement Learning | 2021 | 20 |
| 4 | Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies | 2019 | 2 |
| 5 | Intrinsic motivation and automatic curricula via asymmetric self-play | 2018 | 27 |
| 6 | Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecturebreakdown → | 2015 | 1657 |
| 7 | Weakly Supervised Memory Networks. | 2015 | 42 |
| 8 | Deep neural networks predict category typicality ratings for images | 2015 | 33 |
| 9 | Overfeat: Integrated recognition, localization and detection using convolutional networks. 2nd International Conference on Learning Representations, ICLR 2014 | 2014 | 16 |
| 10 | Learning from Noisy Labels with Deep Neural Networks | 2014 | 4 |
| 11 | Regularization of Neural Networks using DropConnectbreakdown → | 2013 | 957 |
| 12 | Blind Deconvolution with Re-weighted Sparsity Promotion. | 2013 | 10 |
| 13 | Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines | 2011 | 21 |
| 14 | Pose-Sensitive Embedding by Nonlinear NCA Regression | 2010 | 15 |
| 15 | Case for automated detection of diabetic retinopathy | 2010 | 41 |
| 16 | Fast Image Deconvolution using Hyper-Laplacian Priorsbreakdown → | 2009 | 800 |
| 17 | Spectral Hashingbreakdown → | 2008 | 1437 |
| 18 | Small codes and large image databases for recognitionbreakdown → | 2008 | 507 |
| 19 | Object Recognition by Scene Alignment | 2007 | 75 |
| 20 | Sampling Methods for Unsupervised Learning | 2004 | 1 |
About Rob Fergus
Rob Fergus is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence, having authored 63 papers that have together received 22.3k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (21 papers), Image Retrieval and Classification Techniques (13 papers), Advanced Vision and Imaging (12 papers), Domain Adaptation and Few-Shot Learning (10 papers), Image Processing Techniques and Applications (10 papers), Advanced Image Processing Techniques (7 papers), Reinforcement Learning in Robotics (6 papers) and Multimodal Machine Learning Applications (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (16.8k citations), Media Technology (5.2k citations) and Artificial Intelligence (5.5k citations). Rob Fergus has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Pietro Perona, Li Fei-Fei, Antonio Torralba, William T. Freeman, Dilip Krishnan, Matthew D. Zeiler, David Eigen, Yair Weiss, Andrew Zisserman and Graham W. Taylor. Their work appears in journals such as ACM Transactions on Graphics, IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Vision, International Journal of Computer Vision and Proceedings of the IEEE.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.