Bayesian perspectives for quantum states and application to ab initio quantum chemistry | Paper Citation Record

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This paper cites Challenges for Density Functional Theory.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Challenges for Density Functional Theory

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This paper cites Why Is Quantum Chemistry So Complicated?.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Why Is Quantum Chemistry So Complicated?

Reference 2

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This paper cites Spiers Memorial Lecture: Quantum chemistry, clas- sical heuristics, and quantum advantage.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Spiers Memorial Lecture: Quantum chemistry, clas- sical heuristics, and quantum advantage

Reference 3

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This paper cites Elec- tronic Landscape of the P-cluster of Nitrogenase as Revealed through Many- Electron Quantum Wavefunction Simulations.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Elec- tronic Landscape of the P-cluster of Nitrogenase as Revealed through Many- Electron Quantum Wavefunction Simulations

Reference 4

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This paper cites Low-Energy Spectrum of Iron–Sulfur Clusters Directly from Many-Particle Quantum Mechanics.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Low-Energy Spectrum of Iron–Sulfur Clusters Directly from Many-Particle Quantum Mechanics

Reference 5

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This paper cites Entangled Quan- tum Electronic Wavefunctions of the Mn4CaO5 Cluster in Photosystem II.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Entangled Quan- tum Electronic Wavefunctions of the Mn4CaO5 Cluster in Photosystem II

Reference 6

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Unresolved cited work

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This paper cites Flexibilities of wavelets as a computational basis set for large-scale electronic structure calculations.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Flexibilities of wavelets as a computational basis set for large-scale electronic structure calculations

Reference 8

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This paper cites MADNESS: A Multiresolution, Adaptive Numer- ical Environment for Scientific Simulation.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry MADNESS: A Multiresolution, Adaptive Numer- ical Environment for Scientific Simulation

Reference 9

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This paper cites Sliced Basis Density Matrix Renormalization Group for Electronic Structure.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Sliced Basis Density Matrix Renormalization Group for Electronic Structure

Reference 10

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This paper cites From plane waves to local Gaussians for the simulation of corre- lated periodic systems.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry From plane waves to local Gaussians for the simulation of corre- lated periodic systems

Reference 11

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This paper cites Gaussian basis sets for molecular applications.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Gaussian basis sets for molecular applications

Reference 12

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry The updates in Libcint 6: More integrals, API refinements, and SIMD optimization techniques

Reference 13

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This paper cites A priori identification of con- figurational deadwood.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry A priori identification of con- figurational deadwood

Reference 14

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This paper cites Ab-Initio Solution of the Many-Electron Schr ¨odinger Equation with Deep Neural Networks.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Ab-Initio Solution of the Many-Electron Schr ¨odinger Equation with Deep Neural Networks

Reference 15

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Deep-neural-network solution of the electronic Schr¨odinger equation

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Variance extrapolation method for neural-network variational Monte Carlo

Reference 17

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This paper cites Role of Backflow Correlations for the Nonmagnetic Phase of the T-t’ Hubbard Model.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Role of Backflow Correlations for the Nonmagnetic Phase of the T-t’ Hubbard Model

Reference 18

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This paper cites Backflow Correlations in the Hubbard Model: An Efficient Tool for the Study of the Metal-Insulator Transition and the Large-$U$ Limit.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Backflow Correlations in the Hubbard Model: An Efficient Tool for the Study of the Metal-Insulator Transition and the Large-$U$ Limit

Reference 19

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This paper cites Quantum Monte Carlo Approaches for Correlated Systems.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Quantum Monte Carlo Approaches for Correlated Systems

Reference 20

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This paper cites Explicitly Cor- related R12/F12 Methods for Electronic Structure.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Explicitly Cor- related R12/F12 Methods for Electronic Structure

Reference 21

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This paper cites Fermionic neural- network states for ab-initio electronic structure.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Fermionic neural- network states for ab-initio electronic structure

Reference 22

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This paper cites Matrix product operators, matrix product states, and ab initio density matrix renormalization group algorithms.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Matrix product operators, matrix product states, and ab initio density matrix renormalization group algorithms

Reference 23

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This paper cites Unifying neural-network quantum states and correlator product states via tensor networks.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Unifying neural-network quantum states and correlator product states via tensor networks

Reference 24

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Observation f2883634-a0b6-40e0-a974-d0e243b03ab3 · outbound

This paper cites Solving the quantum many-body problem with artificial neural networks.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Solving the quantum many-body problem with artificial neural networks

Reference 25

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This paper cites Chapter 25 - Multiconfigurational quantum chemistry.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Chapter 25 - Multiconfigurational quantum chemistry

Reference 26

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This paper cites Quantum Embedding Theories.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Quantum Embedding Theories

Reference 27

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This paper cites Quantum Embedding Theory for Strongly Correlated States in Materials.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Quantum Embedding Theory for Strongly Correlated States in Materials

Reference 28

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Observation 33b87ed0-c9e1-472f-9fb5-0d98df57efc8 · outbound

This paper cites Systematic Improvability in Quan- tum Embedding for Real Materials.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Systematic Improvability in Quan- tum Embedding for Real Materials

Reference 29

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This paper cites Ab initio effective core potentials for molecular calculations. Potentials for K to Au including the outermost core orbitals.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Ab initio effective core potentials for molecular calculations. Potentials for K to Au including the outermost core orbitals

Reference 30

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This paper cites Canonical transcorrelated theory with projected Slater-type geminals.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Canonical transcorrelated theory with projected Slater-type geminals

Reference 31

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This paper cites A first solution, for LiH, of a molecular transcorrelated wave equation by means of restricted numerical integration.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry A first solution, for LiH, of a molecular transcorrelated wave equation by means of restricted numerical integration

Reference 32

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This paper cites Perspec- tive: Explicitly correlated electronic structure theory for complex systems.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Perspec- tive: Explicitly correlated electronic structure theory for complex systems

Reference 33

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This paper cites Assessment of mul- tireference approaches to explicitly correlated full configuration interaction quantum Monte Carlo.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Assessment of mul- tireference approaches to explicitly correlated full configuration interaction quantum Monte Carlo

Reference 34

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This paper cites An ex- plicitly correlated approach to basis set incompleteness in full configuration interaction quantum Monte Carlo.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry An ex- plicitly correlated approach to basis set incompleteness in full configuration interaction quantum Monte Carlo

Reference 35

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This paper cites Reduced scaling Hilbert space vari- ational Monte Carlo.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Reduced scaling Hilbert space vari- ational Monte Carlo

Reference 36

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This paper cites Bayesian Modelling Approaches for Quantum States - The Ultimate Gaussian Process States Handbook.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Bayesian Modelling Approaches for Quantum States - The Ultimate Gaussian Process States Handbook

Reference 37

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Many-Body Perturbation Theory and Coupled Cluster Theory for Electron Correlation in Molecules

Reference 38

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry State-specific multireference coupled-cluster the- ory

Reference 39

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This paper cites Approximating strongly correlated wave functions with correlator product states.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Approximating strongly correlated wave functions with correlator product states

Reference 40

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Ground-state prop- erties of quantum many-body systems: entangled-plaquette states and vari- ational Monte Carlo

Reference 41

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Gaussian processes for machine learning

Reference 42

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This paper cites Gaussian Process States: A Data-Driven Representation of Quan- tum Many-Body Physics.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Gaussian Process States: A Data-Driven Representation of Quan- tum Many-Body Physics

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This paper cites A Bayesian inference framework for compression and prediction of quantum states.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry A Bayesian inference framework for compression and prediction of quantum states

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This paper cites Learning ground states of gapped quantum Hamiltonians with Kernel Methods.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Reference 45

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Many-Body Problem with Strong Forces

Reference 46

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Error Detecting and Error Correcting Codes

Reference 47

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Additive Gaus- sian Processes

Reference 48

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This paper cites Quantum Gaussian process state: A kernel-inspired state with quantum support data.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Quantum Gaussian process state: A kernel-inspired state with quantum support data

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Observation 2fd3df4a-ccec-4451-aa3c-478c8d60c5d1 · outbound

This paper cites Bayesian Inference: An Introduction to Principles and Practice in Machine Learning.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Bayesian Inference: An Introduction to Principles and Practice in Machine Learning

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry The Relevance Vector Machine

Reference 51

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Fast Marginal Likelihood Maximi- sation for Sparse Bayesian Models

Reference 52

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This paper cites Neural-network quantum state tomography.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Neural-network quantum state tomography

Reference 53

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This paper cites Experimental Online Quantum Dots Charge Autotuning Using Neural Networks.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Experimental Online Quantum Dots Charge Autotuning Using Neural Networks

Reference 54

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This paper cites Neural-network quantum state tomography in a two-qubit experiment.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Neural-network quantum state tomography in a two-qubit experiment

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This paper cites The density-matrix renormalization group in the age of matrix product states.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry The density-matrix renormalization group in the age of matrix product states

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This paper cites Time-evolution methods for matrix-product states.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Time-evolution methods for matrix-product states

Reference 57

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Recent developments in CANDECOMP/PARAFAC algorithms: a critical review

Reference 58

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Tensor Decompositions and Appli- cations

Reference 59

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry CP decom- position for tensors via alternating least squares with QR decomposition

Reference 60

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Observation 80b464df-8492-4f6c-8f82-8ec0b3956e9c · outbound

This paper cites Generalization properties of neural net- work approximations to frustrated magnet ground states.

Bayesian perspectives for quantum states and application to ab initio quantum chemistry Generalization properties of neural net- work approximations to frustrated magnet ground states

Reference 61

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Dirac-Type Nodal Spin Liquid Re- vealed by Refined Quantum Many-Body Solver Using Neural-Network Wave Function, Correlation Ratio, and Level Spectroscopy

Reference 62

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Adam: A Method for Stochastic Optimization

Reference 63

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Neural-network quantum state tomography

Reference 64

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Efficient quantum state tomography with convolutional neural networks

Reference 65

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Attention-Based Transformer Networks for Quantum State Tomogra- phy

Reference 66

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Towards a standardized notation and terminology in multiway analysis

Reference 67

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Impact of condi- tional modelling for a universal autoregressive quantum state

Reference 68

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Helping restricted Boltzmann machines with quantum- state representation by restoring symmetry

Reference 69

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Observation 55803e9a-2a6a-40f9-b2cd-c7a09d55f77d · outbound

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Deep Autoregressive Models for the Efficient Variational Simulation of Many-Body Quantum Systems

Reference 70

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Recurrent neural network wave functions

Reference 71

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Convolutional transformer wave functions

Reference 72

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Pfaf- fian Pairing Wave Functions in Electronic-Structure Quantum Monte Carlo Simulations

Reference 73

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Framework for efficient ab initio elec- tronic structure with Gaussian Process States

Reference 74

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Simple Fermionic backflow states via a systematically improvable tensor decomposition

Reference 75

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Gold-standard solutions to the Schr ¨odinger equation using deep learning: How much physics do we need?

Reference 76

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Solving many-electron Schr¨odinger equation using deep neural networks

Reference 77

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Ab initio quantum chemistry with neural-network wave- functions

Reference 78

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Ab initio calculation of real solids via neural network ansatz

Reference 79

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Backflow Transformations via Neural Networks for Quantum Many-Body Wave Functions

Reference 80

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Neural network backflow for ab initio quantum chemistry

Reference 81

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Efficient optimization of neural network backflow for ab-initio quantum chemistry

Reference 82

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Autoregressive neural-network wavefunctions for ab initio quantum chemistry

Reference 83

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Scalable neural quantum states architecture for quantum chemistry

Reference 84

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry A Real Neural Network State for Quantum Chem- istry

Reference 85

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Artifi- cial Neural Networks Applied as Molecular Wave Function Solvers

Reference 86

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Enhanc- ing the Expressivity of Variational Neural, and Hardware-Efficient Quantum States Through Orbital Rotations

Reference 87

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Strong electronic correlation in the hydrogen chain: A variational Monte 42 Yannic Rath, Massimo Bortone, George H. Booth Carlo study

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Strong cor- relation in hydrogen chains and lattices using the variational two-electron reduced density matrix method

Reference 89

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Observation 12e4822d-6ea2-47ac-a86b-fe07aae0fa59 · outbound

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Towards the Solution of the Many-Electron Problem in Real Materials: Equation of State of the Hydrogen Chain with State-of-the- Art Many-Body Methods

Reference 90

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry On the Non-Orthogonality Problem Connected with the Use of Atomic Wave Functions in the Theory of Molecules and Crystals

Reference 91

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Natural pop- ulation analysis

Reference 92

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Fast noniterative orbital localization for large molecules

Reference 93

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Canonical Configurational Interaction Proce- dure

Reference 94

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Localized Atomic and Molecular Orbitals

Reference 95

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry A fast intrinsic localization procedure applicable for ab initio and semiempirical linear combination of atomic orbital wave functions

Reference 96

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Localized molecular orbitals for polyatomic molecules. I. A com- parison of the Edmiston-Ruedenberg and Boys localization methods

Reference 97

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Quantum Monte Carlo simulations of solids

Reference 98

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Mocking quantum mechanics: Semiclassical and machine- learning approaches to frustrated magnetism

Reference 99

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Bayesian perspectives for quantum states and application to ab initio quantum chemistry Many-body quantum sign structures as non-glassy Ising models

Reference 100

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