StringNET: Neural Network based Variational Method for Transition Pathways
Fuente:
arXiv
Saved in:
| Main Authors: | Han, Jiayue, Gu, Shuting, Zhou, Xiang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Efficient Transition State Searches by Freezing String Method with Graph Neural Network Potentials
by: Marks, Jonah, et al.
Published: (2025)
by: Marks, Jonah, et al.
Published: (2025)
Generating transition states of chemical reactions via distance-geometry-based flow matching
by: Luo, Yufei, et al.
Published: (2025)
by: Luo, Yufei, et al.
Published: (2025)
Effective Dynamics and Transition Pathways from Koopman-Inspired Neural Learning of Collective Variables
by: Sikorski, Alexander, et al.
Published: (2026)
by: Sikorski, Alexander, et al.
Published: (2026)
ChemFlow:A Hierarchical Neural Network for Multiscale Representation Learning in Chemical Mixtures
by: Fan, Jinming, et al.
Published: (2026)
by: Fan, Jinming, et al.
Published: (2026)
Graph Neural Networks for Surfactant Multi-Property Prediction
by: Brozos, Christoforos, et al.
Published: (2024)
by: Brozos, Christoforos, et al.
Published: (2024)
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)
Open-Source Fermionic Neural Networks with Ionic Charge Initialization
by: Pranesh, Shai, et al.
Published: (2024)
by: Pranesh, Shai, et al.
Published: (2024)
Clapeyron Neural Networks for Single-Species Vapor-Liquid Equilibria
by: Pavšek, Jan, et al.
Published: (2026)
by: Pavšek, Jan, et al.
Published: (2026)
Predicting the Temperature Dependence of Surfactant CMCs Using Graph Neural Networks
by: Brozos, Christoforos, et al.
Published: (2024)
by: Brozos, Christoforos, et al.
Published: (2024)
Predicting the Temperature-Dependent CMC of Surfactant Mixtures with Graph Neural Networks
by: Brozos, Christoforos, et al.
Published: (2024)
by: Brozos, Christoforos, 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)
Graph Neural Networks embedded into Margules model for vapor-liquid equilibria prediction
by: Medina, Edgar Ivan Sanchez, et al.
Published: (2025)
by: Medina, Edgar Ivan Sanchez, et al.
Published: (2025)
The Bigger the Better? Accurate Molecular Potential Energy Surfaces from Minimalist Neural Networks
by: Käser, Silvan, et al.
Published: (2024)
by: Käser, Silvan, et al.
Published: (2024)
Graph Neural Networks for Temperature-Dependent Activity Coefficient Prediction of Solutes in Ionic Liquids
by: Rittig, Jan G., et al.
Published: (2022)
by: Rittig, Jan G., et al.
Published: (2022)
Efficient Parallelization of Message Passing Neural Network Potentials for Large-scale Molecular Dynamics
by: Xia, Junfan, et al.
Published: (2025)
by: Xia, Junfan, et al.
Published: (2025)
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
by: Du, Yuanqi, et al.
Published: (2024)
by: Du, Yuanqi, et al.
Published: (2024)
FeNNol: an Efficient and Flexible Library for Building Force-field-enhanced Neural Network Potentials
by: Plé, Thomas, et al.
Published: (2024)
by: Plé, Thomas, et al.
Published: (2024)
Kolmogorov-Arnold Chemical Reaction Neural Networks for learning pressure-dependent kinetic rate laws
by: Koenig, Benjamin C., et al.
Published: (2025)
by: Koenig, Benjamin C., et al.
Published: (2025)
Toward Routine CSP of Pharmaceuticals: A Fully Automated Protocol Using Neural Network Potentials
by: Glick, Zachary L., et al.
Published: (2025)
by: Glick, Zachary L., et al.
Published: (2025)
A Priori Sampling of Transition States with Guided Diffusion
by: Lim, Hyukjun, et al.
Published: (2026)
by: Lim, Hyukjun, et al.
Published: (2026)
Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling and Zero-Shot Transfer
by: Pengmei, Zihan, et al.
Published: (2024)
by: Pengmei, Zihan, et al.
Published: (2024)
Combining Graph Neural Networks and Mixed Integer Linear Programming for Molecular Inference under the Two-Layered Model
by: Zhu, Jianshen, et al.
Published: (2025)
by: Zhu, Jianshen, et al.
Published: (2025)
Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces
by: Gouraud, Nicolaï, et al.
Published: (2026)
by: Gouraud, Nicolaï, et al.
Published: (2026)
GemNet: Universal Directional Graph Neural Networks for Molecules
by: Gasteiger, Johannes, et al.
Published: (2021)
by: Gasteiger, Johannes, et al.
Published: (2021)
$\nabla^2$DFT: A Universal Quantum Chemistry Dataset of Drug-Like Molecules and a Benchmark for Neural Network Potentials
by: Khrabrov, Kuzma, et al.
Published: (2024)
by: Khrabrov, Kuzma, et al.
Published: (2024)
React-OT: Optimal Transport for Generating Transition State in Chemical Reactions
by: Duan, Chenru, et al.
Published: (2024)
by: Duan, Chenru, et al.
Published: (2024)
Predicting performance-related properties of refrigerant based on tailored small-molecule functional group contribution
by: Cao, Peilin, et al.
Published: (2025)
by: Cao, Peilin, et al.
Published: (2025)
Equivariant Matrix Function Neural Networks
by: Batatia, Ilyes, et al.
Published: (2023)
by: Batatia, Ilyes, et al.
Published: (2023)
Neural Network Emulator for Atmospheric Chemical ODE
by: Liu, Zhi-Song, et al.
Published: (2024)
by: Liu, Zhi-Song, 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)
Learning continuous state of charge dependent thermal decomposition kinetics for Li-ion cathodes using Kolmogorov-Arnold Chemical Reaction Neural Networks (KA-CRNNs)
by: Koenig, Benjamin C., et al.
Published: (2025)
by: Koenig, Benjamin C., et al.
Published: (2025)
Pretraining Strategy for Neural Potentials
by: Zhang, Zehua, et al.
Published: (2024)
by: Zhang, Zehua, 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)
Implicit Neural Representations for Chemical Reaction Paths
by: Ramakrishnan, Kalyan, et al.
Published: (2025)
by: Ramakrishnan, Kalyan, 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)
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)
All-atomistic Transferable Neural Potentials for Protein Solvation
by: Dey, Rishabh, et al.
Published: (2026)
by: Dey, Rishabh, et al.
Published: (2026)
Gaussian Plane-Wave Neural Operator for Electron Density Estimation
by: Kim, Seongsu, et al.
Published: (2024)
by: Kim, Seongsu, et al.
Published: (2024)
Accurate Computation of Quantum Excited States with Neural Networks
by: Pfau, David, et al.
Published: (2023)
by: Pfau, David, et al.
Published: (2023)
Similar Items
-
Efficient Transition State Searches by Freezing String Method with Graph Neural Network Potentials
by: Marks, Jonah, et al.
Published: (2025) -
Generating transition states of chemical reactions via distance-geometry-based flow matching
by: Luo, Yufei, et al.
Published: (2025) -
Effective Dynamics and Transition Pathways from Koopman-Inspired Neural Learning of Collective Variables
by: Sikorski, Alexander, et al.
Published: (2026) -
ChemFlow:A Hierarchical Neural Network for Multiscale Representation Learning in Chemical Mixtures
by: Fan, Jinming, et al.
Published: (2026) -
Graph Neural Networks for Surfactant Multi-Property Prediction
by: Brozos, Christoforos, et al.
Published: (2024)