James S. Spencer

DeepMind (United Kingdom) — United Kingdom

Physics and Astronomy · Physical Sciences

20h-index2.0kcitations63works19.02yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Advanced Chemical Physics Studies(24), Machine Learning in Materials Science(16), Catalysis and Oxidation Reactions(8), Physics of Superconductivity and Magnetism(7), Quantum, superfluid, helium dynamics(7)

Publications63 total

Accurate computation of quantum excited states with neural networks
Science·2024· 38 cited
Neural network variational Monte Carlo for positronic chemistry
Nature Communications·2024· 10 citedOpen Access
Neural Wave Functions for Superfluids
Physical Review X·2024· 9 citedOpen Access
Neural network variational Monte Carlo for positronic chemistry
arXiv (Cornell University)·2023Open Access
Accurate Computation of Quantum Excited States with Neural Networks
arXiv (Cornell University)·2023· 5 citedOpen Access
Neural Wave Functions for Superfluids
arXiv (Cornell University)·2023· 1 citedOpen Access
Discovering Quantum Phase Transitions with Fermionic Neural Networks
Physical Review Letters·2023· 71 citedOpen Access
<tt>ipie</tt>: A Python-Based Auxiliary-Field Quantum Monte Carlo Program with Flexibility and Efficiency on CPUs and GPUs
Journal of Chemical Theory and Computation·2022· 23 cited
A Self-Attention Ansatz for Ab-initio Quantum Chemistry
arXiv (Cornell University)·2022· 30 citedOpen Access
Learned Force Fields Are Ready For Ground State Catalyst Discovery
arXiv (Cornell University)·2022· 15 citedOpen Access
ipie: A Python-based Auxiliary-Field Quantum Monte Carlo Program with Flexibility and Efficiency on CPUs and GPUs
arXiv (Cornell University)·2022Open Access
Ab-initio quantum chemistry with neural-network wavefunctions
arXiv (Cornell University)·2022· 11 citedOpen Access
Response to Comment on “Pushing the frontiers of density functionals by solving the fractional electron problem”
Science·2022· 6 citedOpen Access
Discovering Quantum Phase Transitions with Fermionic Neural Networks
arXiv (Cornell University)·2022· 3 citedOpen Access
Pushing the frontiers of density functionals by solving the fractional electron problem
Science·2021· 373 citedOpen Access
Learning many-electron wavefunctions with deep neural networks
Nature Reviews Physics·2021· 3 cited
Better, Faster Fermionic Neural Networks
arXiv (Cornell University)·2020· 7 citedOpen Access
Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural Networks
Bulletin of the American Physical Society·2020· 2 cited
Research data and further information supporting "Large Scale Parallelization in Stochastic Coupled Cluster"
Apollo (University of Cambridge)·2019Open Access
Research Data and Further Information supporting "The HANDE-QMC project: open-source stochastic quantum chemistry from the ground state up"
Apollo (University of Cambridge)·2019Open Access
page 1 of 4Next →

Frequent Co-authors

W. M. C. Foulkes(18), David Pfau(14), Alex J. W. Thom(10), W. A. Vigor(7), Fionn D. Malone(6), James J. Shepherd(6), Gino Cassella(6), Halvard Sutterud(6), Nick S. Blunt(5), R. S. T. Franklin(4), Alexander L. Gaunt(3), Ali Alavi(3), Verena A. Neufeld(3), Simon Axelrod(3), Ingrid von Glehn(3), Michael J. Bearpark(3), Michael R. Crusoe(2), Hussien F. Alameldin(2), Sherine Awad(2), Adam Caldwell(2)