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Forward Laplacian: A New Computational Framework for Neural
  Network-based Variational Monte Carlo

Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo

17 July 2023
Rui Li
Hao-Tong Ye
Du Jiang
Xuelan Wen
Chuwei Wang
Zhe Li
Xiang Li
Di He
Ji Chen
Weiluo Ren
Liwei Wang
ArXivPDFHTML

Papers citing "Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo"

5 / 5 papers shown
Title
Is attention all you need to solve the correlated electron problem?
Is attention all you need to solve the correlated electron problem?
Max Geier
Khachatur Nazaryan
Timothy Zaklama
Liang Fu
33
2
0
07 Feb 2025
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
Zekun Shi
Zheyuan Hu
Min-Bin Lin
Kenji Kawaguchi
104
4
0
27 Nov 2024
Gold-standard solutions to the Schrödinger equation using deep
  learning: How much physics do we need?
Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?
Leon Gerard
Michael Scherbela
P. Marquetand
Philipp Grohs
AI4CE
35
34
0
19 May 2022
Explicitly antisymmetrized neural network layers for variational Monte
  Carlo simulation
Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation
Jeffmin Lin
Gil Goldshlager
Lin Lin
35
22
0
07 Dec 2021
Deep neural network solution of the electronic Schrödinger equation
Deep neural network solution of the electronic Schrödinger equation
J. Hermann
Zeno Schätzle
Frank Noé
141
444
0
16 Sep 2019
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