David Eigende@deigen.netI 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 InfoPreviously, 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.
|
|