Robert C. Fergus
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Robert C. Ferguscomputer-science Degrees
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Computer Science
Robert C. Fergus's Degrees
- PhD Computer Science University of California, Berkeley
- Masters Computer Science University of California, Berkeley
- Bachelors Computer Science University of California, Berkeley
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Why Is Robert C. Fergus Influential?
(Suggest an Edit or Addition)Robert C. Fergus's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Visualizing and Understanding Convolutional Networks (2013) (13463)
- Intriguing properties of neural networks (2013) (10943)
- Learning Spatiotemporal Features with 3D Convolutional Networks (2014) (6389)
- OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks (2013) (4704)
- Indoor Segmentation and Support Inference from RGBD Images (2012) (4209)
- Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories (2004) (3961)
- Depth Map Prediction from a Single Image using a Multi-Scale Deep Network (2014) (2938)
- One-shot learning of object categories (2006) (2680)
- Spectral Hashing (2008) (2562)
- Object class recognition by unsupervised scale-invariant learning (2003) (2524)
- Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture (2014) (2308)
- Regularization of Neural Networks using DropConnect (2013) (2291)
- End-To-End Memory Networks (2015) (2221)
- Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks (2015) (2055)
- 80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition (2008) (2007)
- Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation (2014) (1448)
- Image and depth from a conventional camera with a coded aperture (2007) (1426)
- Deconvolutional networks (2010) (1375)
- Fast Image Deconvolution using Hyper-Laplacian Priors (2009) (1251)
- Adaptive deconvolutional networks for mid and high level feature learning (2011) (1140)
- Blind deconvolution using a normalized sparsity measure (2011) (1002)
- Removing camera shake from a single photograph (2006) (932)
- Stochastic Pooling for Regularization of Deep Convolutional Neural Networks (2013) (915)
- Learning object categories from Google's image search (2005) (846)
- Learning Multiagent Communication with Backpropagation (2016) (835)
- Small codes and large image databases for recognition (2008) (807)
- Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences (2019) (776)
- Convolutional Learning of Spatio-temporal Features (2010) (664)
- A Bayesian approach to unsupervised one-shot learning of object categories (2003) (635)
- Training Convolutional Networks with Noisy Labels (2014) (551)
- Visualizing and Understanding Convolutional Neural Networks (2013) (519)
- Indoor scene segmentation using a structured light sensor (2011) (514)
- Stochastic Video Generation with a Learned Prior (2018) (426)
- Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels (2020) (420)
- Restoring an Image Taken through a Window Covered with Dirt or Rain (2013) (386)
- C3D: Generic Features for Video Analysis (2014) (374)
- A sparse object category model for efficient learning and exhaustive recognition (2005) (354)
- Learning invariant features through topographic filter maps (2009) (353)
- A Visual Category Filter for Google Images (2004) (339)
- Simple Baseline for Visual Question Answering (2015) (301)
- Learning Physical Intuition of Block Towers by Example (2016) (282)
- Semi-Supervised Learning in Gigantic Image Collections (2009) (279)
- Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play (2017) (254)
- Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition (2007) (246)
- Improving Sample Efficiency in Model-Free Reinforcement Learning from Images (2019) (237)
- Learning from Noisy Labels with Deep Neural Networks (2014) (211)
- Multidimensional Spectral Hashing (2012) (168)
- Modeling Others using Oneself in Multi-Agent Reinforcement Learning (2018) (152)
- Beyond frontal faces: Improving Person Recognition using multiple cues (2015) (148)
- Offline Reinforcement Learning with Fisher Divergence Critic Regularization (2021) (146)
- Semantic Label Sharing for Learning with Many Categories (2010) (145)
- Understanding Deep Architectures using a Recursive Convolutional Network (2013) (134)
- Object Recognition by Scene Alignment (2007) (132)
- Dark flash photography (2009) (130)
- Learning Binary Hash Codes for Large-Scale Image Search (2013) (125)
- Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks (2016) (124)
- Deep End2End Voxel2Voxel Prediction (2015) (114)
- Reinforcement Learning with Prototypical Representations (2021) (108)
- Random Lens Imaging (2006) (105)
- Weakly Supervised Memory Networks (2015) (105)
- Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning (2021) (103)
- Learning Simple Algorithms from Examples (2015) (98)
- End-to-end integration of a Convolutional Network, Deformable Parts Model and non-maximum suppression (2014) (94)
- Improving Image Classification with Location Context (2015) (92)
- Instance Segmentation of Indoor Scenes Using a Coverage Loss (2014) (89)
- Learning Object Categories From Internet Image Searches (2010) (88)
- Nonparametric image parsing using adaptive neighbor sets (2012) (84)
- User Conditional Hashtag Prediction for Images (2015) (84)
- Web scale photo hash clustering on a single machine (2015) (80)
- Automatic Data Augmentation for Generalization in Deep Reinforcement Learning (2020) (79)
- MazeBase: A Sandbox for Learning from Games (2015) (77)
- Case for Automated Detection of Diabetic Retinopathy (2010) (69)
- Deep Neural Networks Predict Category Typicality Ratings for Images (2015) (68)
- Tiny images (2007) (67)
- Learning by Asking Questions (2017) (63)
- IntPhys: A Framework and Benchmark for Visual Intuitive Physics Reasoning (2018) (53)
- Learning to Discover Efficient Mathematical Identities (2014) (52)
- Composable Planning with Attributes (2018) (52)
- Learning invariance through imitation (2011) (52)
- Decoupling Value and Policy for Generalization in Reinforcement Learning (2021) (48)
- Automatic Data Augmentation for Generalization in Reinforcement Learning (2021) (41)
- A Hybrid Neural Network-Latent Topic Model (2012) (41)
- Energy-based models for atomic-resolution protein conformations (2020) (40)
- Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines (2011) (39)
- Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning (2018) (33)
- Pose-Sensitive Embedding by Nonlinear NCA Regression (2010) (30)
- Visual object category recognition (2005) (29)
- Deep Poselets for Human Detection (2014) (27)
- Finding Generalizable Evidence by Learning to Convince Q&A Models (2019) (25)
- A Sparse Object Category Model for Efficient Learning and Complete Recognition (2006) (24)
- Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies (2019) (17)
- Fast Adaptation to New Environments via Policy-Dynamics Value Functions (2020) (17)
- Blind Deconvolution with Non-local Sparsity Reweighting (2013) (15)
- Differentiable Pooling for Hierarchical Feature Learning (2012) (14)
- Blind Deconvolution with Re-weighted Sparsity Promotion (2013) (14)
- Object and scene recognition in tiny images (2010) (13)
- Deep End 2 End Voxel 2 Voxel Prediction (2018) (11)
- Efficient methods for object recognition using the constellation model (2001) (10)
- IntPhys 2019: A Benchmark for Visual Intuitive Physics Understanding (2019) (10)
- Fast Adaptation via Policy-Dynamics Value Functions (2020) (10)
- Deconvolutional Networks for Feature Learning (2010) (9)
- Learning Image Decompositions with Hierarchical Sparse Coding (2010) (7)
- Collaborating with language models for embodied reasoning (2023) (5)
- Understanding the Asymptotic Performance of Model-Based RL Methods (2018) (5)
- Imitation by Predicting Observations (2021) (5)
- Sampling Methods for Unsupervised Learning (2004) (3)
- Balancing information exposure in social networks (2018) (3)
- Teacher Guided Training: An Efficient Framework for Knowledge Transfer (2022) (2)
- Semi-supervised learning and recognition of object classes (2004) (1)
- The Influence of the Eighteenth Novel of Justinian. II (1897) (1)
- EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval (2023) (1)
- Disentangling Video with Independent Prediction (2019) (1)
- Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC (2023) (1)
- Distilling Internet-Scale Vision-Language Models into Embodied Agents (2023) (0)
- Learning Object Categories From Internet Image Searches This paper shows how the results returned by an image search engine can be used to construct models from Internet images and use them for object recognition. (2010) (0)
- Low-level Image Priors and Laplacian Preconditioners for Applications in Computer Graphics and Computational Photography (2013) (0)
- B IOLOGICAL S TRUCTURE AND F UNCTION E MERGE FROM S CALING U NSUPERVISED L EARNING TO 250 M ILLION P ROTEIN S EQUENCES (2019) (0)
- Fergus' Directory of the City of Chicago 1839 (0)
- 2 Deconvolution using a Gaussian Prior (2007) (0)
- Learning binary projections for large scale image search (2011) (0)
- Accelerating exploration and representation learning with offline pre-training (2023) (0)
- Metric learning by active crowdsourcing (0)
- Bayesian Compression for Deep Learning (2017) (0)
- UvA-DARE (Digital Academic Repository) Causal Effect Inference with Deep Latent-Variable Models (2017) (0)
- International Journal of Innovative Technology and Exploring Engineering (IJITEE) (2019) (0)
- Scry Me a River (2011) (0)
- Perturbing BatchNorm and Only BatchNorm Benefits Sharpness-Aware Minimization (2022) (0)
- Learning to Navigate Wikipedia by Taking Random Walks (2022) (0)
- Session details: Computational photography (2010) (0)
- Past Oxford Robotics Research Group Seminars (2008) (0)
- Differentiable pooling for hierarchical feature learning: arXiv 1207.0151v1 (2012) (0)
- UvA-DARE (Digital Academic Repository) Causal Effect Inference with Deep Latent-Variable Models Causal Effect Inference with Deep Latent-Variable Models (2017) (0)
- Empirically Verifying Hypotheses Using Reinforcement Learning (2020) (0)
- Differentially private Bayesian learning on distributed data Heikkila (0)
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