Variational Monte Carlo

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Most implemented papers archive 2025-07-28

24 shown of 24 papers with code (55 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Transferable Neural Wavefunctions for Solids
  13 May 2024 4 repositories listed
  To mitigate this problem, recent research has proposed optimizing a single neural network across multiple systems, reducing the cost per system.
• Towards a Foundation Model for Neural Network Wavefunctions
  17 Mar 2023 4 repositories listed
  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…
• Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation
  12 Mar 2024 2 repositories listed
  Understanding the real-time evolution of many-electron quantum systems is essential for studying dynamical properties in condensed matter, quantum chemistry, and complex materials, yet it poses a significant theoretical…
• Accurate Computation of Quantum Excited States with Neural Networks
  31 Aug 2023 2 repositories listed Syntology ran 10 of 13 samples · 3 unverified
  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.
• Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo
  17 Jul 2023 2 repositories listed
  Neural network-based variational Monte Carlo (NN-VMC) has emerged as a promising cutting-edge technique of ab initio quantum chemistry.
• Deep autoregressive models for the efficient variational simulation of many-body quantum systems
  11 Feb 2019 2 repositories listed Syntology ran 0 of 14 samples · 14 unverified
  Artificial Neural Networks were recently shown to be an efficient representation of highly-entangled many-body quantum states.
• Solving Statistical Mechanics Using Variational Autoregressive Networks
  27 Sep 2018 2 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  We propose a general framework for solving statistical mechanics of systems with finite size.
• Spectral Inference Networks: Unifying Deep and Spectral Learning
  6 Jun 2018 2 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  We present Spectral Inference Networks, a framework for learning eigenfunctions of linear operators by stochastic optimization.
• Hyperbolic recurrent neural network as the first type of non-Euclidean neural quantum state ansatz
  28 May 2025 1 repository listed
  Furthermore, in settings where the Hamiltonian displays a clear hierarchical interaction structure, such as the 1D Heisenberg J₁J₂ & J₁J₂J₃ systems with the 1st, 2nd and even 3rd nearest neighbor interactions, our…
• A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions
  18 Jan 2024 1 repository listed
  Neural network wavefunctions optimized using the variational Monte Carlo method have been shown to produce highly accurate results for the electronic structure of atoms and small molecules, but the high cost of…
• Variational optimization of the amplitude of neural-network quantum many-body ground states
  18 Aug 2023 1 repository listed
  Here, we split a quantum many-body variational wave function into a multiplication of a real-valued amplitude neural network and a sign structure, and focus on the optimization of the amplitude network while keeping the…
• Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions
  15 Jul 2023 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  Obtaining accurate solutions to the Schr\"odinger equation is the key challenge in computational quantum chemistry.
• From Tensor Network Quantum States to Tensorial Recurrent Neural Networks
  24 Jun 2022 1 repository listed
  We show that any matrix product state (MPS) can be exactly represented by a recurrent neural network (RNN) with a linear memory update.
• Variational Monte Carlo Approach to Partial Differential Equations with Neural Networks
  4 Jun 2022 1 repository listed
  The accurate numerical solution of partial differential equations is a central task in numerical analysis allowing to model a wide range of natural phenomena by employing specialized solvers depending on the scenario of…
• Discovering Quantum Phase Transitions with Fermionic Neural Networks
  10 Feb 2022 1 repository listed
  Deep neural networks have been extremely successful as highly accurate wave function ans\"atze for variational Monte Carlo calculations of molecular ground states.
• NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems
  20 Dec 2021 1 repository listed Syntology ran 0 of 8 samples · 8 unverified
  We introduce version 3 of NetKet, the machine learning toolbox for many-body quantum physics.
• Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation
  7 Dec 2021 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  We then consider a factorized antisymmetric (FA) layer which more directly generalizes the FermiNet by replacing products of determinants with products of antisymmetrized neural networks.
• Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions
  11 Oct 2021 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Solving the Schr\"odinger equation is key to many quantum mechanical properties.
• Autoregressive neural-network wavefunctions for ab initio quantum chemistry
  26 Sep 2021 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  In recent years, neural network quantum states (NNQS) have emerged as powerful tools for the study of quantum many-body systems.
• Continuous-variable neural-network quantum states and the quantum rotor model
  15 Jul 2021 1 repository listed
  We initiate the study of neural-network quantum state algorithms for analyzing continuous-variable lattice quantum systems in first quantization.
• Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks
  12 May 2021 1 repository listed Syntology ran 0 of 7 samples · 7 unverified
  Efficient sampling of complex high-dimensional probability distributions is a central task in computational science.
• Convergence to the fixed-node limit in deep variational Monte Carlo
  11 Oct 2020 1 repository listed
  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.
• Natural evolution strategies and variational Monte Carlo
  9 May 2020 1 repository listed
  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.
• Streaming Variational Monte Carlo
  4 Jun 2019 1 repository listed Syntology ran 0 of 12 samples · 12 unverified
  Nonlinear state-space models are powerful tools to describe dynamical structures in complex time series.

Syntology lines on 11 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.