44 citations · 82 across the 5 of their papers we have counts for
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cs.LG2023★ 30 cited
Uncertainty Quantification for Molecular Property Predictions with Graph Neural Architecture Search
Shengli Jiang, Shiyi Qin, Reid C. Van Lehn +2
Graph Neural Networks (GNNs) have emerged as a prominent class of data-driven methods for molecular property prediction. However, a key limitation of typical GNN models is their in…
cs.LG2021★ 44 cited
Convolutional Neural Nets in Chemical Engineering: Foundations, Computations, and Applications
Shengli Jiang, Victor M. Zavala
In this paper we review the mathematical foundations of convolutional neural nets (CNNs) with the goals of: i) highlighting connections with techniques from statistics, signal proc…
cs.LG2020★ 5 cited
Graph Neural Network Architecture Search for Molecular Property Prediction
Shengli Jiang, Prasanna Balaprakash
Predicting the properties of a molecule from its structure is a challenging task. Recently, deep learning methods have improved the state of the art for this task because of their…