COCO Attributes: Attributes for People, Animals, and Objects

1 code implementation • ECCV 2016 • Genevieve Patterson, James Hays

In this paper, we discover and annotate visual attributes for the COCO dataset.

Attribute Object

Expert identification of visual primitives used by CNNs during mammogram classification

1 code implementation • 13 Mar 2018 • Jimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester Mackey, Genevieve Patterson

This work interprets the internal representations of deep neural networks trained for classification of diseased tissue in 2D mammograms.

Classification General Classification

DeepMiner: Discovering Interpretable Representations for Mammogram Classification and Explanation

1 code implementation • 31 May 2018 • Jimmy Wu, Bolei Zhou, Diondra Peck, Scott Hsieh, Vandana Dialani, Lester Mackey, Genevieve Patterson

We propose DeepMiner, a framework to discover interpretable representations in deep neural networks and to build explanations for medical predictions.

Classification General Classification +1

Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops

2 code implementations • 8 Feb 2019 • Limor Gultchin, Genevieve Patterson, Nancy Baym, Nathaniel Swinger, Adam Tauman Kalai

While humor is often thought to be beyond the reach of Natural Language Processing, we show that several aspects of single-word humor correlate with simple linear directions in Word Embeddings.

Clustering Word Embeddings

RNNbow: Visualizing Learning via Backpropagation Gradients in Recurrent Neural Networks

no code implementations • 29 Jul 2019 • Dylan Cashman, Genevieve Patterson, Abigail Mosca, Nathan Watts, Shannon Robinson, Remco Chang

RNNbow is a web application that displays the relative gradient contributions from Recurrent Neural Network (RNN) cells in a neighborhood of an element of a sequence.