On Representing Electronic Wave Functions with Sign Equivariant Neural Networks
Fuente:
arXiv
Saved in:
| Main Authors: | Gao, Nicholas, Günnemann, Stephan |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
by: Gao, Nicholas, et al.
Published: (2024)
by: Gao, Nicholas, et al.
Published: (2024)
Learning Equivariant Non-Local Electron Density Functionals
by: Gao, Nicholas, et al.
Published: (2024)
by: Gao, Nicholas, et al.
Published: (2024)
Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State
by: Gao, Nicholas, et al.
Published: (2026)
by: Gao, Nicholas, et al.
Published: (2026)
Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems
by: Scherbela, Michael, et al.
Published: (2025)
by: Scherbela, Michael, et al.
Published: (2025)
GemNet: Universal Directional Graph Neural Networks for Molecules
by: Gasteiger, Johannes, et al.
Published: (2021)
by: Gasteiger, Johannes, et al.
Published: (2021)
Accurate Computation of Quantum Excited States with Neural Networks
by: Pfau, David, et al.
Published: (2023)
by: Pfau, David, et al.
Published: (2023)
High-Rank Irreducible Cartesian Tensor Decomposition and Bases of Equivariant Spaces
by: Shao, Shihao, et al.
Published: (2024)
by: Shao, Shihao, et al.
Published: (2024)
Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement
by: Yescas-Ramos, Zuriel Y., et al.
Published: (2026)
by: Yescas-Ramos, Zuriel Y., et al.
Published: (2026)
Equivariant Matrix Function Neural Networks
by: Batatia, Ilyes, et al.
Published: (2023)
by: Batatia, Ilyes, et al.
Published: (2023)
Consistent Sampling and Simulation: Molecular Dynamics with Energy-Based Diffusion Models
by: Plainer, Michael, et al.
Published: (2025)
by: Plainer, Michael, et al.
Published: (2025)
Analysis of Atom-level pretraining with Quantum Mechanics (QM) data for Graph Neural Networks Molecular property models
by: Arjona-Medina, Jose, et al.
Published: (2024)
by: Arjona-Medina, Jose, et al.
Published: (2024)
Neural Quantum States and Peaked Molecular Wave Functions: Curse or Blessing?
by: Malyshev, Aleksei, et al.
Published: (2024)
by: Malyshev, Aleksei, et al.
Published: (2024)
Neural Polarization: Toward Electron Density for Molecules by Extending Equivariant Networks
by: Kwak, Bumju, et al.
Published: (2024)
by: Kwak, Bumju, et al.
Published: (2024)
Spectral Densities, Structured Noise and Ensemble Averaging within Open Quantum Dynamics
by: Holtkamp, Yannick Marcel, et al.
Published: (2024)
by: Holtkamp, Yannick Marcel, et al.
Published: (2024)
Quantum Dynamics via Score Matching on Bohmian Trajectories
by: Wang, Lei
Published: (2026)
by: Wang, Lei
Published: (2026)
Symmetry-invariant quantum machine learning force fields
by: Le, Isabel Nha Minh, et al.
Published: (2023)
by: Le, Isabel Nha Minh, et al.
Published: (2023)
Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks
by: Thiemann, Fabian L., et al.
Published: (2025)
by: Thiemann, Fabian L., et al.
Published: (2025)
Learning Non-Local Molecular Interactions via Equivariant Local Representations and Charge Equilibration
by: Fuchs, Paul, et al.
Published: (2025)
by: Fuchs, Paul, et al.
Published: (2025)
Gaussian Plane-Wave Neural Operator for Electron Density Estimation
by: Kim, Seongsu, et al.
Published: (2024)
by: Kim, Seongsu, et al.
Published: (2024)
Broadening the Scope of Neural Network Potentials through Direct Inclusion of Additional Molecular Attributes
by: Simeon, Guillem, et al.
Published: (2024)
by: Simeon, Guillem, et al.
Published: (2024)
QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials
by: Zariquiey, Francesc Sabanés, et al.
Published: (2025)
by: Zariquiey, Francesc Sabanés, et al.
Published: (2025)
Assessing the Limits of Graph Neural Networks for Vapor-Liquid Equilibrium Prediction: A Cryogenic Mixture Case Study
by: Gupta, Aryan
Published: (2025)
by: Gupta, Aryan
Published: (2025)
Implicit Delta Learning of High Fidelity Neural Network Potentials
by: Thaler, Stephan, et al.
Published: (2024)
by: Thaler, Stephan, et al.
Published: (2024)
Highly Accurate Real-space Electron Densities with Neural Networks
by: Cheng, Lixue, et al.
Published: (2024)
by: Cheng, Lixue, et al.
Published: (2024)
Self-consistent Validation for Machine Learning Electronic Structure
by: Hu, Gengyuan, et al.
Published: (2024)
by: Hu, Gengyuan, et al.
Published: (2024)
Shadow Ansatz for the Many-Fermion Wave Function in Scalable Molecular Simulations on Quantum Computing Devices
by: Wang, Yuchen, et al.
Published: (2024)
by: Wang, Yuchen, et al.
Published: (2024)
chemtrain: Learning Deep Potential Models via Automatic Differentiation and Statistical Physics
by: Fuchs, Paul, et al.
Published: (2024)
by: Fuchs, Paul, et al.
Published: (2024)
chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations
by: Fuchs, Paul, et al.
Published: (2025)
by: Fuchs, Paul, et al.
Published: (2025)
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations
by: Pelaez, Raul P., et al.
Published: (2024)
by: Pelaez, Raul P., et al.
Published: (2024)
NeuralSCF: Neural network self-consistent fields for density functional theory
by: Song, Feitong, et al.
Published: (2024)
by: Song, Feitong, et al.
Published: (2024)
Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields
by: Liao, Yi-Lun, et al.
Published: (2024)
by: Liao, Yi-Lun, et al.
Published: (2024)
Integrating Machine Learning and Quantum Circuits for Proton Affinity Predictions
by: Jin, Hongni, et al.
Published: (2024)
by: Jin, Hongni, et al.
Published: (2024)
Parametrized Quantum Circuit Learning for Quantum Chemical Applications
by: Jones, Grier M., et al.
Published: (2025)
by: Jones, Grier M., et al.
Published: (2025)
The Convergence Frontier: Integrating Machine Learning and High Performance Quantum Computing for Next-Generation Drug Discovery
by: Ansari, Narjes, et al.
Published: (2026)
by: Ansari, Narjes, et al.
Published: (2026)
Generative flow-based warm start of the variational quantum eigensolver
by: Zou, Hang, et al.
Published: (2025)
by: Zou, Hang, et al.
Published: (2025)
Using machine learning to map simulated noisy and laser-limited multidimensional spectra to molecular electronic couplings
by: Schultz, Jonathan D., et al.
Published: (2025)
by: Schultz, Jonathan D., et al.
Published: (2025)
Diagonalization without Diagonalization: A Direct Optimization Approach for Solid-State Density Functional Theory
by: Li, Tianbo, et al.
Published: (2024)
by: Li, Tianbo, et al.
Published: (2024)
Quantum Computation of Electronic Structure with Projector Augmented-Wave Method and Plane Wave Basis Set
by: Ivanov, Aleksei V., et al.
Published: (2024)
by: Ivanov, Aleksei V., et al.
Published: (2024)
Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation
by: Nys, Jannes, et al.
Published: (2024)
by: Nys, Jannes, et al.
Published: (2024)
Thermodynamic Transferability in Coarse-Grained Force Fields using Graph Neural Networks
by: Shinkle, Emily, et al.
Published: (2024)
by: Shinkle, Emily, et al.
Published: (2024)
Similar Items
-
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
by: Gao, Nicholas, et al.
Published: (2024) -
Learning Equivariant Non-Local Electron Density Functionals
by: Gao, Nicholas, et al.
Published: (2024) -
Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State
by: Gao, Nicholas, et al.
Published: (2026) -
Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems
by: Scherbela, Michael, et al.
Published: (2025) -
GemNet: Universal Directional Graph Neural Networks for Molecules
by: Gasteiger, Johannes, et al.
Published: (2021)