112 citations · 280 across the 9 of their papers we have counts for
9 papers
Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information
Yulun Wu, Robert A. Barton, Zichen Wang +5
Predicting the responses of a cell under perturbations may bring important benefits to drug discovery and personalized therapeutics. In this work, we propose a novel graph variatio…
Model-free Sign Estimation for High-Throughput Screenings
Jackson Loper, Jeffrey Regier
In high-throughput screenings, it is common to estimate the effects of many treatments using a small number of independent trials of each. Because little is known about the distrib…
Neural Design for Genetic Perturbation Experiments
Aldo Pacchiano, Drausin Wulsin, Robert A. Barton +1
The problem of how to genetically modify cells in order to maximize a certain cellular phenotype has taken center stage in drug development over the last few years (with, for examp…
Hypergraph Pre-training with Graph Neural Networks
Boxin Du, Changhe Yuan, Robert Barton +2
Despite the prevalence of hypergraphs in a variety of high-impact applications, there are relatively few works on hypergraph representation learning, most of which primarily focus…
Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution
Robert A. Barton, Tal Neiman, Changhe Yuan
Online stores often utilize product relationships such as bundles and substitutes to improve their catalog quality and guide customers through myriad choices. Entity resolution usi…
Simultaneous Electrical and Optical Readout of Graphene-Coated High Q Silicon Nitride Resonators
V. P. Adiga, R. De Alba, I. R. Storch +8
We have fabricated and tested mechanical resonators consisting of a single-atomic-layer of graphene deposited on suspended silicon nitride membranes. With the addition of the graph…