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Books and Theses
- 2015
[b1]David Eigen:
Predicting Images using Convolutional Networks: Visual Scene Understanding with Pixel Maps. New York University, USA, 2015
Journal Articles
- 2024
- [j2]Constance Dubois
, David Eigen, François Simon, Vincent Couloigner, Michael Gormish, Martin Chalumeau, Laurent Schmoll, Jérémie F. Cohen:
Development and validation of a smartphone-based deep-learning-enabled system to detect middle-ear conditions in otoscopic images. npj Digit. Medicine 7(1) (2024) - 2021
- [j1]Amir Erfan Eshratifar, David Eigen, Michael Gormish, Massoud Pedram:
Coarse2Fine: a two-stage training method for fine-grained visual classification. Mach. Vis. Appl. 32(2): 49 (2021)
Conference and Workshop Papers
- 2020
- [c14]Mohammad Saeed Abrishami, Amir Erfan Eshratifar, David Eigen, Yanzhi Wang, Shahin Nazarian, Massoud Pedram:
Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space. ISQED 2020: 347-351 - 2019
- [c13]Amir Erfan Eshratifar, Mohammad Saeed Abrishami, David Eigen, Massoud Pedram:
A Meta-Learning Approach for Custom Model Training. AAAI 2019: 9937-9938 - [c12]Hongyang Li, David Eigen, Samuel Dodge, Matthew Zeiler, Xiaogang Wang:
Finding Task-Relevant Features for Few-Shot Learning by Category Traversal. CVPR 2019: 1-10 - 2015
- [c11]Li Wan, David Eigen, Rob Fergus:
End-to-end integration of a Convolutional Network, Deformable Parts Model and non-maximum suppression. CVPR 2015: 851-859 - [c10]David Eigen, Rob Fergus:
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture. ICCV 2015: 2650-2658 - [c9]Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun:
Unsupervised Learning of Spatiotemporally Coherent Metrics. ICCV 2015: 4086-4093 - [c8]Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun:
Unsupervised Feature Learning from Temporal Data. ICLR (Workshop) 2015 - 2014
- [c7]David Eigen, Christian Puhrsch, Rob Fergus:
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network. NIPS 2014: 2366-2374 - [c6]David Eigen, Jason Tyler Rolfe, Rob Fergus, Yann LeCun:
Understanding Deep Architectures using a Recursive Convolutional Network. ICLR (Workshop Poster) 2014 - [c5]David Eigen, Marc'Aurelio Ranzato, Ilya Sutskever:
Learning Factored Representations in a Deep Mixture of Experts. ICLR (Workshop Poster) 2014 - [c4]Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, Yann LeCun:
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks. ICLR 2014 - 2013
- [c3]David Eigen, Dilip Krishnan, Rob Fergus:
Restoring an Image Taken through a Window Covered with Dirt or Rain. ICCV 2013: 633-640 - 2012
- [c2]David Eigen, Rob Fergus:
Nonparametric image parsing using adaptive neighbor sets. CVPR 2012: 2799-2806 - 2004
- [c1]David Eigen, Daniel H. Grollman, David H. Laidlaw, Benjamin D. Greenberg, Erin Einbinder:
Visualizing deep brain stimulation settings in obsessive compulsive disorder. SIGGRAPH Posters 2004: 110
Informal and Other Publications
- 2024
- [i10]Michael J. Bianco, David Eigen, Michael Gormish:
Enhancing Worldwide Image Geolocation by Ensembling Satellite-Based Ground-Level Attribute Predictors. CoRR abs/2407.13862 (2024) - 2020
- [i9]Mohammad Saeed Abrishami, Amir Erfan Eshratifar, David Eigen, Yanzhi Wang, Shahin Nazarian, Massoud Pedram:
Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space. CoRR abs/2002.04776 (2020) - 2019
- [i8]Hongyang Li, David Eigen, Samuel Dodge, Matthew Zeiler, Xiaogang Wang:
Finding Task-Relevant Features for Few-Shot Learning by Category Traversal. CoRR abs/1905.11116 (2019) - [i7]Amir Erfan Eshratifar, David Eigen, Michael Gormish, Massoud Pedram:
Coarse2Fine: A Two-stage Training Method for Fine-grained Visual Classification. CoRR abs/1909.02680 (2019) - 2018
- [i6]Amir Erfan Eshratifar, Mohammad Saeed Abrishami, David Eigen, Massoud Pedram:
A Meta-Learning Approach for Custom Model Training. CoRR abs/1809.08346 (2018) - [i5]Amir Erfan Eshratifar, David Eigen, Massoud Pedram:
Gradient Agreement as an Optimization Objective for Meta-Learning. CoRR abs/1810.08178 (2018) - 2014
- [i4]David Eigen, Christian Puhrsch, Rob Fergus:
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network. CoRR abs/1406.2283 (2014) - [i3]David Eigen, Rob Fergus:
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture. CoRR abs/1411.4734 (2014) - [i2]Li Wan, David Eigen, Rob Fergus:
End-to-End Integration of a Convolutional Network, Deformable Parts Model and Non-Maximum Suppression. CoRR abs/1411.5309 (2014) - [i1]Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun:
Unsupervised Learning of Spatiotemporally Coherent Metrics. CoRR abs/1412.6056 (2014)
Coauthor Index
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