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Jackson W. Burns

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Open access Oct 2026

Causal-Chemprop: Causal Machine Learning for Molecular Property Prediction and Design

A priori estimation of molecular properties has long been a topic of immense interest to the pharmaceutical sciences for molecular design. While neural network-based models have achieved high predictive accuracy, they have limited utility in molecular design, particularly in small and out-of-distribution data regimes...

Christian Natajaya, L. Attia, Jackson W. Burns et al. · 0 citations
Aug 2026

Deep Learning Foundation Models for Low-Data Regimes from Classical Molecular Descriptors.

This work proposes pretraining on low-noise, calculable molecular descriptors via supervised learning to obtain rich, highly transferable molecular representations and demonstrates this strategy with CheMeleon, a O(10M) parameter foundation model that enables directed message-passing neural networks to finally exceed t...

Jackson W. Burns, Akshat Shirish Zalte, C. Abreu et al. · 1 citation

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