David Eigen

According to our database, David Eigen authored at least 17 papers between 2004 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Coarse2Fine: a two-stage training method for fine-grained visual classification.

Amir Erfan Eshratifar, David Eigen, Michael Gormish, Massoud Pedram

Mach. Vis. Appl., 2021

2020

Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space.

Mohammad Saeed Abrishami, Amir Erfan Eshratifar, David Eigen, Yanzhi Wang, Shahin Nazarian, Massoud Pedram

Proceedings of the 21st International Symposium on Quality Electronic Design, 2020

2019

Finding Task-Relevant Features for Few-Shot Learning by Category Traversal.

Hongyang Li, David Eigen, Samuel Dodge, Matthew Zeiler, Xiaogang Wang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

A Meta-Learning Approach for Custom Model Training.

Amir Erfan Eshratifar, Mohammad Saeed Abrishami, David Eigen, Massoud Pedram

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Gradient Agreement as an Optimization Objective for Meta-Learning.

Amir Erfan Eshratifar, David Eigen, Massoud Pedram

CoRR, 2018

2015

Predicting Images using Convolutional Networks: Visual Scene Understanding with Pixel Maps.

David Eigen

PhD thesis, 2015

Unsupervised Feature Learning from Temporal Data.

Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

Proceedings of the 3rd International Conference on Learning Representations, 2015

Unsupervised Learning of Spatiotemporally Coherent Metrics.

Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture.

David Eigen, Rob Fergus

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

End-to-end integration of a Convolutional Network, Deformable Parts Model and non-maximum suppression.

Li Wan, David Eigen, Rob Fergus

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks.

Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, Yann LeCun

Proceedings of the 2nd International Conference on Learning Representations, 2014

Learning Factored Representations in a Deep Mixture of Experts.

David Eigen, Marc'Aurelio Ranzato, Ilya Sutskever

Proceedings of the 2nd International Conference on Learning Representations, 2014

Understanding Deep Architectures using a Recursive Convolutional Network.

David Eigen, Jason Tyler Rolfe, Rob Fergus, Yann LeCun

Proceedings of the 2nd International Conference on Learning Representations, 2014

Depth Map Prediction from a Single Image using a Multi-Scale Deep Network.

David Eigen, Christian Puhrsch, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Restoring an Image Taken through a Window Covered with Dirt or Rain.

David Eigen, Dilip Krishnan, Rob Fergus

Proceedings of the IEEE International Conference on Computer Vision, 2013

2012

Nonparametric image parsing using adaptive neighbor sets.

David Eigen, Rob Fergus

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2004

Visualizing deep brain stimulation settings in obsessive compulsive disorder.

David Eigen, Daniel H. Grollman, David H. Laidlaw, Benjamin D. Greenberg, Erin Einbinder

Proceedings of the International Conference on Computer Graphics and Interactive Techniques, 2004