84 citations · 130 across the 7 of their papers we have counts for
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physics.comp-ph2023
Neural network variational Monte Carlo for positronic chemistry
G. Cassella, W. M. C. Foulkes, D. Pfau +1
Quantum chemical calculations of the ground-state properties of positron-molecule complexes are challenging. The main difficulty lies in employing an appropriate basis set for repr…
physics.comp-ph2022★ 84 cited
Discovering Quantum Phase Transitions with Fermionic Neural Networks
G. Cassella, H. Sutterud, S. Azadi +4
Deep neural networks have been extremely successful as highly accurate wave function ansätze for variational Monte Carlo calculations of molecular ground states. We present an exte…