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Found 3 papers, 3 papers with code
DQC: a Python program package for Differentiable Quantum Chemistry
Automatic differentiation represents a paradigm shift in scientific programming, where evaluating both functions and their derivatives is required for most applications.
Learning the exchange-correlation functional from nature with fully differentiable density functional theory
Improving the predictive capability of molecular properties in ab initio simulations is essential for advanced material discovery.
$ξ$-torch: differentiable scientific computing library
In this work, we present $\xi$-torch, a library of differentiable functionals for scientific simulations.
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