Publications (33)
Learning Physical Intuition of Block Towers by Example
Adam Lerer, Sam Gross, Rob Fergus
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
Pierre Sermanet, David Eigen, Xiang Zhang +3
Understanding Deep Architectures using a Recursive Convolutional Network
David Eigen, Jason Rolfe, Rob Fergus +1
Visualizing and Understanding Convolutional Networks
Matthew D Zeiler, Rob Fergus
End-To-End Memory Networks
Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston +1
S4: A Spatial-Spectral model for Speckle Suppression
Rob Fergus, David W. Hogg, Rebecca Oppenheimer +2
Learning by Asking Questions
Ishan Misra, Ross Girshick, Rob Fergus +3
Maximizing Kepler science return per telemetered pixel: Searching the habitable zones of the brightest stars
Benjamin T. Montet, Ruth Angus, Tom Barclay +9
Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues
Ning Zhang, Manohar Paluri, Yaniv Taigman +2
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks
Matthew D. Zeiler, Rob Fergus
Simple Baseline for Visual Question Answering
Bolei Zhou, Yuandong Tian, Sainbayar Sukhbaatar +2
Improving Image Classification with Location Context
Kevin Tang, Manohar Paluri, Li Fei-Fei +2
Blind Deconvolution with Non-local Sparsity Reweighting
Dilip Krishnan, Joan Bruna, Rob Fergus
Maximizing Kepler science return per telemetered pixel: Detailed models of the focal plane in the two-wheel era
David W. Hogg, Ruth Angus, Tom Barclay +9
End-to-End Integration of a Convolutional Network, Deformable Parts Model and Non-Maximum Suppression
Li Wan, David Eigen, Rob Fergus
Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning
Sainbayar Sukhbaatar, Emily Denton, Arthur Szlam +1
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture
David Eigen, Rob Fergus
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
Roberta Raileanu, Emily Denton, Arthur Szlam +1
MazeBase: A Sandbox for Learning from Games
Sainbayar Sukhbaatar, Arthur Szlam, Gabriel Synnaeve +2
Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play
Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov +3
Disentangling Video with Independent Prediction
William F. Whitney, Rob Fergus
Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever +4
Differentiable Pooling for Hierarchical Feature Learning
Matthew D. Zeiler, Rob Fergus
Deep Poselets for Human Detection
Lubomir Bourdev, Fei Yang, Rob Fergus
Learning Spatiotemporal Features with 3D Convolutional Networks
Du Tran, Lubomir Bourdev, Rob Fergus +2
Learning Multiagent Communication with Backpropagation
Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
David Eigen, Christian Puhrsch, Rob Fergus
Learning Simple Algorithms from Examples
Wojciech Zaremba, Tomas Mikolov, Armand Joulin +1
Composable Planning with Attributes
Amy Zhang, Adam Lerer, Sainbayar Sukhbaatar +2
Deep End2End Voxel2Voxel Prediction
Du Tran, Lubomir Bourdev, Rob Fergus +2
Training Convolutional Networks with Noisy Labels
Sainbayar Sukhbaatar, Joan Bruna, Manohar Paluri +2
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
Emily Denton, Soumith Chintala, Arthur Szlam +1
Learning to Discover Efficient Mathematical Identities
Wojciech Zaremba, Karol Kurach, Rob Fergus