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Fermionic neural network (FermiNet) is a recently proposed wavefunction Ansatz, which is used in variational Monte Carlo (VMC) methods to solve the many-electron Schr\"{o}dinger equation.
Inhomogeneous electron gas
Pierre Hohenberg and Walter Kohn · 1964
Earlier work this paper cites.
Monte carlo sampling methods using markov chains and their applications
W Keith Hastings · 1970
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Multilayer feedforward networks are universal approximators
Kurt Hornik, Maxwell Stinchcombe, and Halbert White · 1989
Earlier work this paper cites.
Fermion nodes
David M Ceperley · 1991
Earlier work this paper cites.
Density-functional thermochemistry. i. the effect of the exchange-only gradient correction
Axel D Becke · 1992
Earlier work this paper cites.
Ground-state correlation energies for atomic ions with 3 to 18 electrons
Subhas J Chakravorty, Steven R Gwaltney, Ernest R Davidson, Farid A Parpia, and Charlotte Froese p Fischer · 1993
Earlier work this paper cites.
Local-density-approximation prediction of electronic properties of gan, si, c, and ruo 2
GL Zhao, D Bagayoko, and TD Williams · 1999
Earlier work this paper cites.
A long-range correction scheme for generalized-gradient-approximation exchange functionals
Hisayoshi Iikura, Takao Tsuneda, Takeshi Yanai, and Kimihiko Hirao · 2001
Earlier work this paper cites.
Better, faster fermionic neural networks, 2020
James S. Spencer, David Pfau, Aleksandar Botev, and W. M.C. Foulkes · 2011
Earlier work this paper cites.
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B Keimer and JE Moore · 2017
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Solving many-electron schrödinger equation using deep neural networks
Jiequn Han, Linfeng Zhang, and E Weinan · 2019
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Deep-neural-network solution of the electronic schrödinger equation
Jan Hermann, Zeno Schätzle, and Frank Noé · 2020
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Ab initio solution of the many-electron schrödinger equation with deep neural networks
David Pfau, James S Spencer, Alexander GDG Matthews, and W Matthew C Foulkes · 2020
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Phases of two-dimensional spinless lattice fermions with first-quantized deep neural-network quantum states
James Stokes, Javier Robledo Moreno, Eftychios A Pnevmatikakis, and Giuseppe Carleo · 2020
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Neural network wave functions and the sign problem
Attila Szabó and Claudio Castelnovo · 2020
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Geometric deep learning on molecular representations
Kenneth Atz, Francesca Grisoni, and Gisbert Schneider · 2021
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Ab-initio potential energy surfaces by pairing gnns with neural wave functions
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Fermionic neural-network states for ab-initio electronic structure
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Quantum mechanics in drug discovery
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Determinant-free fermionic wave function using feed-forward neural networks
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Convergence to the fixed-node limit in deep variational monte carlo
Zeno Schätzle, Jan Hermann, and Frank Noé · 2021
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Equivariant transformers for neural network based molecular potentials
Philipp Thölke and Gianni De Fabritiis · 2022
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