Muhammad Firmansyah Kasim

Qi Zhu

Joshua Selfridge

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Unifying physical systems' inductive biases in neural ODE using dynamics constraints.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

2022

Building high accuracy emulators for scientific simulations with deep neural architecture search.

[BibT_eX]

[DOI]

Jacob Topp-Mugglestone

Eleonora Viezzer

Mach. Learn. Sci. Technol., 2022

Constants of motion network.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Reducing the Long Tail Losses in Scientific Emulations with Active Learning.

[BibT_eX]

[DOI]

CoRR, 2021

DQC: a Python program package for Differentiable Quantum Chemistry.

[BibT_eX]

[DOI]

Susi Lehtola

CoRR, 2021

Learning the exchange-correlation functional from nature with fully differentiable density functional theory.

[BibT_eX]

[DOI]

CoRR, 2021

2020

Derivatives of partial eigendecomposition of a real symmetric matrix for degenerate cases.

[BibT_eX]

[DOI]

CoRR, 2020

ξ-torch: differentiable scientific computing library.

[BibT_eX]

[DOI]

CoRR, 2020

Up to two billion times acceleration of scientific simulations with deep neural architecture search.

[BibT_eX]

[DOI]

Jacob Topp-Mugglestone

Eleonora Viezzer

CoRR, 2020

2019

Efficient Parameter Sampling for Neural Network Construction.

[BibT_eX]

[DOI]

Drimik Roy Chowdhury