Variational Monte Carlo
19 papers with code • 0 benchmarks • 0 datasets
Variational methods for quantum physics
Benchmarks
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Most implemented papers
Towards a Foundation Model for Neural Network Wavefunctions
Furthermore, we provide ample experimental evidence to support the idea that extensive pre-training of a such a generalized wavefunction model across different compounds and geometries could lead to a foundation wavefunction model.
Spectral Inference Networks: Unifying Deep and Spectral Learning
deepmind/spectral_inference_networks
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ICLR 2019
We present Spectral Inference Networks, a framework for learning eigenfunctions of linear operators by stochastic optimization.
Solving Statistical Mechanics Using Variational Autoregressive Networks
We propose a general framework for solving statistical mechanics of systems with finite size.
Deep autoregressive models for the efficient variational simulation of many-body quantum systems
Artificial Neural Networks were recently shown to be an efficient representation of highly-entangled many-body quantum states.
Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo
ywolfeee/lapjax
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Neural network-based variational Monte Carlo (NN-VMC) has emerged as a promising cutting-edge technique of ab initio quantum chemistry.
Natural Quantum Monte Carlo Computation of Excited States
We present a variational Monte Carlo algorithm for estimating the lowest excited states of a quantum system which is a natural generalization of the estimation of ground states.
Streaming Variational Monte Carlo
catniplab/svmc
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Nonlinear state-space models are powerful tools to describe dynamical structures in complex time series.
Natural evolution strategies and variational Monte Carlo
Ericolony/QAOA
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A notion of quantum natural evolution strategies is introduced, which provides a geometric synthesis of a number of known quantum/classical algorithms for performing classical black-box optimization.
Convergence to the fixed-node limit in deep variational Monte Carlo
deepqmc/deepqmc
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Variational quantum Monte Carlo (QMC) is an ab-initio method for solving the electronic Schr\"odinger equation that is exact in principle, but limited by the flexibility of the available ansatzes in practice.
Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks
wdphy16/neural-cluster-update
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Efficient sampling of complex high-dimensional probability distributions is a central task in computational science.
