9 citations · 17 across the 7 of their papers we have counts for
4 papers · 1 filter
Active learning for affinity prediction of antibodies
Alexandra Gessner, Sebastian W. Ober, Owen Vickery +2
The primary objective of most lead optimization campaigns is to enhance the binding affinity of ligands. For large molecules such as antibodies, identifying mutations that enhance…
NESS: Node Embeddings from Static SubGraphs
Talip Ucar
We present a framework for learning Node Embeddings from Static Subgraphs (NESS) using a graph autoencoder (GAE) in a transductive setting. NESS is based on two key ideas: i) Parti…
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning
Talip Ucar, Ehsan Hajiramezanali, Lindsay Edwards
Self-supervised learning has been shown to be very effective in learning useful representations, and yet much of the success is achieved in data types such as images, audio, and te…
Bridging the ELBO and MMD
Talip Ucar
One of the challenges in training generative models such as the variational auto encoder (VAE) is avoiding posterior collapse. When the generator has too much capacity, it is prone…