David Eigen

de@deigen.net

Curriculum Vitae

I am currently a research scientist at Clarifai.

My research areas are computer vision and machine learning. I graduated with a PhD in Computer Science from NYU in 2015; my advisor was Rob Fergus.



Papers & Publications

Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space
Mohammad Saeed Abrishami, Amir Erfan Eshratifar, David Eigen, Yanzhi Wang, Shahin Nazarian and Massoud Pedram
ArXiv Preprint 2020 (pdf)
Finding Task-Relevant Features for Few-Shot Learning by Category Traversal
Hongyang Li, David Eigen, Samuel Dodge, Matthew Zeiler and Xiaogang Wang
CVPR 2019 (pdf) (github)
A Meta-Learning Approach for Custom Model Training
Amir Erfan Eshratifar, Mohammad Saeed Abrishami, David Eigen and Massoud Pedram
AAAI Student Abstract Track 2019 (pdf)
Gradient Agreement as an Optimization Objective for Meta-Learning
Amir Erfan Eshratifar, David Eigen and Massoud Pedram
NeurIPS Meta-Learning Workshop 2018 (pdf)
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture
David Eigen and Rob Fergus
ICCV 2015 (pdf)
Predicting Images using Convolutional Networks: Visual Scene Understanding with Pixel Maps
PhD Thesis, 2015 (pdf)
Unsupervised Learning of Spatiotemporally Coherent Metrics
Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen and Yann LeCun
ICCV 2015 (pdf)
End-to-End Integration of a Convolutional Network, Deformable Parts Model and Non-Maximum Suppression
Li Wan, David Eigen and Rob Fergus
CVPR 2015 (pdf)
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
David Eigen, Christian Puhrsch and Rob Fergus
NIPS 2014 (pdf)
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
Pierre Sermanet, David Eigen, Xiang Zhang, Michael Mathieu, Rob Fergus and Yann LeCun
ICLR 2014 (pdf)
Learning Factored Representations in a Deep Mixture of Experts
David Eigen, Marc'Aurelio Ranzato and Ilya Sutskever
ICLR Workshops 2014 (pdf)
Understanding Deep Architectures using a Recursive Convolutional Network
David Eigen, Jason Rolfe, Rob Fergus and Yann LeCun
ICLR Workshops 2014 (pdf)
Restoring An Image Taken Through a Window Covered with Dirt or Rain
David Eigen, Dilip Krishnan and Rob Fergus
ICCV 2013 (pdf)
Nonparametric Image Parsing using Adaptive Neighbor Sets
David Eigen and Rob Fergus
CVPR 2012 (pdf)


Other Info

Previously, I was working on antispam and antimalware at Cisco IronPort Systems.

Before IronPort, I was at NetApp, where I worked on the WAFL filesystem and rewrote much of the NVLog intent journal. Before that, I was at Brown, where I studied math, computer science and cognitive science.

At Brown, I developed a set of visualization tools for differential geometry with Prof. Banchoff. This has since been applied to more applications and labs over the past few years; one of the latest complements the textbook "Differential Geometry of Curves and Surfaces" by Banchoff and Lovett.

For Burning Man '09, I made a large jigsaw puzzle.

Projects older than those on my CV are here. This includes selected final projects from various classes.