49 citations · 55 across the 7 of their papers we have counts for
3 papers · 1 filter
Uncertainty separation via ensemble quantile regression
Navid Ansari, Hans-Peter Seidel, Vahid Babaei
This paper introduces a novel and scalable framework for uncertainty estimation and separation with applications in data driven modeling in science and engineering tasks where reli…
Two-Stage Pretraining for Molecular Property Prediction in the Wild
Kevin Tirta Wijaya, Minghao Guo, Michael Sun +3
Molecular deep learning models have achieved remarkable success in property prediction, but they often require large amounts of labeled data. The challenge is that, in real-world a…
TrustMol: Trustworthy Inverse Molecular Design via Alignment with Molecular Dynamics
Kevin Tirta Wijaya, Navid Ansari, Hans-Peter Seidel +1
Data-driven generation of molecules with desired properties, also known as inverse molecular design (IMD), has attracted significant attention in recent years. Despite the signific…