202 citations · 211 across the 5 of their papers we have counts for
5 papers
Limeade: Let integer molecular encoding aid
Shiqiang Zhang, Christian W. Feldmann, Frederik Sandfort +3
Mixed-integer programming (MIP) is a well-established framework for computer-aided molecular design (CAMD). By precisely encoding the molecular space and score functions, e.g., a g…
Transformers for molecular property prediction: Lessons learned from the past five years
Afnan Sultan, Jochen Sieg, Miriam Mathea +1
Molecular Property Prediction (MPP) is vital for drug discovery, crop protection, and environmental science. Over the last decades, diverse computational techniques have been devel…
Augmenting optimization-based molecular design with graph neural networks
Shiqiang Zhang, Juan S. Campos, Christian Feldmann +3
Computer-aided molecular design (CAMD) studies quantitative structure-property relationships and discovers desired molecules using optimization algorithms. With the emergence of ma…
Optimizing over trained GNNs via symmetry breaking
Shiqiang Zhang, Juan S. Campos, Christian Feldmann +5
Optimization over trained machine learning models has applications including: verification, minimizing neural acquisition functions, and integrating a trained surrogate into a larg…
Analyzing Learned Molecular Representations for Property Prediction
Kevin Yang, Kyle Swanson, Wengong Jin +12
Advancements in neural machinery have led to a wide range of algorithmic solutions for molecular property prediction. Two classes of models in particular have yielded promising res…