Luca Thiede

Materials Science · Physical Sciences

6h-index213citations23works5.82yr avg
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Research Topics

Machine Learning in Materials Science(14), Computational Drug Discovery Methods(9), Advanced Chemical Physics Studies(3), Protein Structure and Dynamics(3), Advanced Electron Microscopy Techniques and Applications(2)

Publications23 total

Coupled Cluster con MōLe: Molecular Orbital Learning for Neural Wavefunctions
ArXiv.org·2026Open Access
Coupled Cluster con MōLe: Molecular Orbital Learning for Neural Wavefunctions
arXiv (Cornell University)·2026Open Access
Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink
ArXiv.org·2026Open Access
Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink
arXiv (Cornell University)·2026Open Access
DEQuify your force field: More efficient simulations using deep equilibrium models
arXiv (Cornell University)·2025Open Access
ELECTRA: A Cartesian Network for 3D Charge Density Prediction with Floating Orbitals
arXiv (Cornell University)·2025Open Access
Waveflow: Boundary-conditioned normalizing flows applied to fermionic wave functions
APL Machine Learning·2024· 1 citedOpen Access
Spiers Memorial Lecture: How to do impactful research in artificial intelligence for chemistry and materials science
Faraday Discussions·2024· 11 citedOpen Access
In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back
Advanced Materials·2024· 57 citedOpen Access
In silico chemical experiments in the Age of AI: From quantum chemistry to machine learning and back
2024· 1 cited
Author response for "Towards equilibrium molecular conformation generation with GFlowNets"
2024
In silico chemical experiments in the Age of AI: From quantum chemistry to machine learning and back
2024· 2 citedOpen Access
Towards equilibrium molecular conformation generation with GFlowNets
Digital Discovery·2024· 2 citedOpen Access
Sorting Out Quantum Monte Carlo
arXiv (Cornell University)·2023· 1 citedOpen Access
Towards equilibrium molecular conformation generation with GFlowNets
arXiv (Cornell University)·2023Open Access
Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation
arXiv (Cornell University)·2023· 3 citedOpen Access
Waveflow: boundary-conditioned normalizing flows applied to fermionic wavefunctions
arXiv (Cornell University)·2022Open Access
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design
arXiv (Cornell University)·2022· 28 citedOpen Access
Curiosity in exploring chemical spaces: intrinsic rewards for molecular reinforcement learning
Machine Learning Science and Technology·2022· 18 citedOpen Access
Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning
arXiv (Cornell University)·2020· 11 citedOpen Access
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Frequent Co-authors

Alán Aspuru‐Guzik(11), Abdulrahman Aldossary(4), Sergio Pablo‐García(4), Shi Xuan Leong(4), Gary Tom(4), Jorge A. Campos-Gonzalez-Angulo(3), Ella Miray Rajaonson(3), Andrew Z. Wang(3), Davide Avagliano(3), AkshatKumar Nigam(3), Alán Aspuru-Guzik(3), Alexandra Volokhova(3), Michał Koziarski(3), Chenghao Liu(3), Santiago Miret(3), Pablo Lemos(3), Zichao Yan(3), Mario Krenn(2), Andreas Burger(2), Pratik Prabhanjan Brahma(2)