activity
20182021
collaborators

5 papers

cs.LG2021

Diffusion Earth Mover's Distance and Distribution Embeddings

Alexander Tong, Guillaume Huguet, Amine Natik +5

We propose a new fast method of measuring distances between large numbers of related high dimensional datasets called the Diffusion Earth Mover's Distance (EMD). We model the datas…

stat.ML2020

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics

Alexander Tong, Jessie Huang, Guy Wolf +2

It is increasingly common to encounter data from dynamic processes captured by static cross-sectional measurements over time, particularly in biomedical settings. Recent attempts t…

cs.LG2019

Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators

Alexander Tong, Guy Wolf, Smita Krishnaswamy

Anomaly detection is of great interest in fields where abnormalities need to be identified and corrected (e.g., medicine and finance). Deep learning methods for this task often rel…

cs.LG2019

Finding Archetypal Spaces Using Neural Networks

David van Dijk, Daniel Burkhardt, Matthew Amodio +3

Archetypal analysis is a data decomposition method that describes each observation in a dataset as a convex combination of "pure types" or archetypes. These archetypes represent ex…

cs.LG2018

Interpretable Neuron Structuring with Graph Spectral Regularization

Alexander Tong, David van Dijk, Jay S. Stanley +6

While neural networks are powerful approximators used to classify or embed data into lower dimensional spaces, they are often regarded as black boxes with uninterpretable features.…