5 citations · 17 across the 7 of their papers we have counts for
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cs.LG2025★ 3 cited
AlphaNet: Scaling Up Local-frame-based Atomistic Interatomic Potential
Bangchen Yin, Jiaao Wang, Weitao Du +9
Molecular dynamics simulations demand an unprecedented combination of accuracy and scalability to tackle grand challenges in catalysis and materials design. To bridge this gap, we…
cs.LG2024★ 2 cited
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
Yuanqi Du, Michael Plainer, Rob Brekelmans +5
Rare event sampling in dynamical systems is a fundamental problem arising in the natural sciences, which poses significant computational challenges due to an exponentially large sp…
cs.LG2024
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
Lingkai Kong, Yuanqi Du, Wenhao Mu +8
Addressing real-world optimization problems becomes particularly challenging when analytic objective functions or constraints are unavailable. While numerous studies have addressed…