Publications (24)
New Benchmarks for Learning on Non-Homophilous Graphs
Derek Lim, Xiuyu Li, Felix Hohne +1
Much data with graph structures satisfy the principle of homophily, meaning that connected nodes tend to be similar with respect to a specific attribute. As such, ubiquitous datase…
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
Derek Lim, Theo Moe Putterman, Robin Walters +2
Many algorithms and observed phenomena in deep learning appear to be affected by parameter symmetries -- transformations of neural network parameters that do not change the underly…
Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform
Derek Lim, Austin R. Benson
Many platforms collect crowdsourced information primarily from volunteers. As this type of knowledge curation has become widespread, contribution formats vary substantially and are…
Equivariant Manifold Flows
Isay Katsman, Aaron Lou, Derek Lim +3
Tractably modelling distributions over manifolds has long been an important goal in the natural sciences. Recent work has focused on developing general machine learning models to l…
Spectra of Convex Hulls of Matrix Groups
Eric Jankowski, Charles R. Johnson, Derek Lim
The still-unsolved problem of determining the set of eigenvalues realized by -by- doubly stochastic matrices, those matrices with row sums and column sums equal to , has a…
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning
Sharut Gupta, Joshua Robinson, Derek Lim +2
Self-supervised learning converts raw perceptual data such as images to a compact space where simple Euclidean distances measure meaningful variations in data. In this paper, we ex…