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Variational Monte Carlo
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Variational methods for quantum physics
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Hyperbolic recurrent neural network as the first type of non-Euclidean neural quantum state ansatz
Improving Energy Natural Gradient Descent through Woodbury, Momentum, and Randomization
Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems
Diagonal Symmetrization of Neural Network Solvers for the Many-Electron Schrödinger Equation
Is attention all you need to solve the correlated electron problem?
Generalized Lanczos method for systematic optimization of neural-network quantum states
Retentive Neural Quantum States: Efficient Ansätze for Ab Initio Quantum Chemistry
A Theoretical Framework for an Efficient Normalizing Flow-Based Solution to the Electronic Schrodinger Equation
Transferable Neural Wavefunctions for Solids
Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation
A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions
Open-Source Fermionic Neural Networks with Ionic Charge Initialization
Pairing-based graph neural network for simulating quantum materials
Accurate Computation of Quantum Excited States with Neural Networks
Variational optimization of the amplitude of neural-network quantum many-body ground states
Neural-network quantum state study of the long-range antiferromagnetic Ising chain
Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo
Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions
NNQS-Transformer: an Efficient and Scalable Neural Network Quantum States Approach for Ab initio Quantum Chemistry
Neural Wave Functions for Superfluids
Convergence of variational Monte Carlo simulation and scale-invariant pre-training
Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators
Towards a Foundation Model for Neural Network Wavefunctions
Towards Neural Variational Monte Carlo That Scales Linearly with System Size
Understanding and eliminating spurious modes in variational Monte Carlo using collective variables
Gauge Equivariant Neural Networks for 2+1D U(1) Gauge Theory Simulations in Hamiltonian Formulation
Toward Neural Network Simulation of Variational Quantum Algorithms
Neural network quantum state with proximal optimization: a ground-state searching scheme based on variational Monte Carlo
From Tensor Network Quantum States to Tensorial Recurrent Neural Networks
An Empirical Study of Quantum Dynamics as a Ground State Problem with Neural Quantum States
Variational Monte Carlo Approach to Partial Differential Equations with Neural Networks
$O(N^2)$ Universal Antisymmetry in Fermionic Neural Networks
Machine learning predictions for local electronic properties of disordered correlated electron systems
Electronic excited states in deep variational Monte Carlo
Discovering Quantum Phase Transitions with Fermionic Neural Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.