papers
Publications (11)
cs.LG2019
A Meta-Learning Approach for Custom Model Training
Amir Erfan Eshratifar, Mohammad Saeed Abrishami, David Eigen +1
cs.CV2015
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture
David Eigen, Rob Fergus
cs.CV2019
Finding Task-Relevant Features for Few-Shot Learning by Category Traversal
Hongyang Li, David Eigen, Samuel Dodge +2
cs.CV2015
Unsupervised Learning of Spatiotemporally Coherent Metrics
Ross Goroshin, Joan Bruna, Jonathan Tompson +2
cs.CV2014
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
David Eigen, Christian Puhrsch, Rob Fergus
cs.LG2014
Learning Factored Representations in a Deep Mixture of Experts
David Eigen, Marc'Aurelio Ranzato, Ilya Sutskever
cs.CV2014
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
Pierre Sermanet, David Eigen, Xiang Zhang +3
cs.LG2018
Gradient Agreement as an Optimization Objective for Meta-Learning
Amir Erfan Eshratifar, David Eigen, Massoud Pedram
cs.CV2015
Unsupervised Feature Learning from Temporal Data
Ross Goroshin, Joan Bruna, Jonathan Tompson +2
cs.CV2014
End-to-End Integration of a Convolutional Network, Deformable Parts Model and Non-Maximum Suppression
Li Wan, David Eigen, Rob Fergus
cs.LG2014
Understanding Deep Architectures using a Recursive Convolutional Network
David Eigen, Jason Rolfe, Rob Fergus +1