2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.LG2025★ 2 cited
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
Zekun Shi, Zheyuan Hu, Min Lin +1
Optimizing neural networks with loss that contain high-dimensional and high-order differential operators is expensive to evaluate with back-propagation due to …
physics.chem-ph2024
Diagonalization without Diagonalization: A Direct Optimization Approach for Solid-State Density Functional Theory
Tianbo Li, Min Lin, Stephen Dale +4
We present a novel approach to address the challenges of variable occupation numbers in direct optimization of density functional theory (DFT). By parameterizing both the eigenfunc…
cs.PL2023
Automatic Functional Differentiation in JAX
Min Lin
We extend JAX with the capability to automatically differentiate higher-order functions (functionals and operators). By representing functions as a generalization of arrays, we sea…