Split-Flows: Measure Transport and Information Loss Across Molecular Resolutions
Fuente:
arXiv
Guardado en:
| Autores principales: | Hummerich, Sander, Bereau, Tristan, Köthe, Ullrich |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Adversarial reverse mapping of condensed-phase molecular structures: Chemical transferability
por: Stieffenhofer, Marc, et al.
Publicado: (2021)
por: Stieffenhofer, Marc, et al.
Publicado: (2021)
Navigating Chemical Space: Multi-Level Bayesian Optimization with Hierarchical Coarse-Graining
por: Walter, Luis J., et al.
Publicado: (2025)
por: Walter, Luis J., et al.
Publicado: (2025)
Energy-Based Coarse-Graining in Molecular Dynamics: A Flow-Based Framework without Data
por: Stupp, Maximilian, et al.
Publicado: (2025)
por: Stupp, Maximilian, et al.
Publicado: (2025)
Fokker-Planck Score Learning: Efficient Free-Energy Estimation under Periodic Boundary Conditions
por: Nagel, Daniel, et al.
Publicado: (2025)
por: Nagel, Daniel, et al.
Publicado: (2025)
Data-Efficient Multidimensional Free Energy Estimation via Physics-Informed Score Learning
por: Nagel, Daniel, et al.
Publicado: (2026)
por: Nagel, Daniel, et al.
Publicado: (2026)
EquiFlow: Equivariant Conditional Flow Matching with Optimal Transport for 3D Molecular Conformation Prediction
por: Tian, Qingwen, et al.
Publicado: (2024)
por: Tian, Qingwen, et al.
Publicado: (2024)
Learning Distributions on Manifolds with Free-Form Flows
por: Sorrenson, Peter, et al.
Publicado: (2023)
por: Sorrenson, Peter, et al.
Publicado: (2023)
Molecular Learning Dynamics
por: Gusev, Yaroslav, et al.
Publicado: (2025)
por: Gusev, Yaroslav, et al.
Publicado: (2025)
FEAT: Free energy Estimators with Adaptive Transport
por: He, Jiajun, et al.
Publicado: (2025)
por: He, Jiajun, et al.
Publicado: (2025)
Teaching Molecular Dynamics to a Non-Autoregressive Ionic Transport Predictor
por: Kim, Jiyeon, et al.
Publicado: (2026)
por: Kim, Jiyeon, et al.
Publicado: (2026)
Operator Forces For Coarse-Grained Molecular Dynamics
por: Klein, Leon, et al.
Publicado: (2025)
por: Klein, Leon, et al.
Publicado: (2025)
Molecular relaxation by reverse diffusion with time step prediction
por: Kahouli, Khaled, et al.
Publicado: (2024)
por: Kahouli, Khaled, et al.
Publicado: (2024)
Grappa -- A Machine Learned Molecular Mechanics Force Field
por: Seute, Leif, et al.
Publicado: (2024)
por: Seute, Leif, et al.
Publicado: (2024)
Learning Non-Local Molecular Interactions via Equivariant Local Representations and Charge Equilibration
por: Fuchs, Paul, et al.
Publicado: (2025)
por: Fuchs, Paul, et al.
Publicado: (2025)
Broadening the Scope of Neural Network Potentials through Direct Inclusion of Additional Molecular Attributes
por: Simeon, Guillem, et al.
Publicado: (2024)
por: Simeon, Guillem, et al.
Publicado: (2024)
Efficient Implementation of Gaussian Process Regression Accelerated Saddle Point Searches with Application to Molecular Reactions
por: Goswami, Rohit, et al.
Publicado: (2025)
por: Goswami, Rohit, et al.
Publicado: (2025)
Enabling Structure-Only Initialization and Out-of-Distribution Generalization in GNN-based Molecular Dynamics Simulators
por: Shteingolts, S. A., et al.
Publicado: (2026)
por: Shteingolts, S. A., et al.
Publicado: (2026)
Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State
por: Gao, Nicholas, et al.
Publicado: (2026)
por: Gao, Nicholas, et al.
Publicado: (2026)
Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow
por: Cao, Zhonglin, et al.
Publicado: (2025)
por: Cao, Zhonglin, et al.
Publicado: (2025)
Hessian Matching for Machine-Learned Coarse-Grained Molecular Dynamics
por: Murdeshwar, Sanya, et al.
Publicado: (2026)
por: Murdeshwar, Sanya, et al.
Publicado: (2026)
Lifting Architectural Constraints of Injective Flows
por: Sorrenson, Peter, et al.
Publicado: (2023)
por: Sorrenson, Peter, et al.
Publicado: (2023)
Electron-Informed Coarse-Graining Molecular Representation Learning for Real-World Molecular Physics
por: Na, Gyoung S., et al.
Publicado: (2026)
por: Na, Gyoung S., et al.
Publicado: (2026)
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations
por: Pelaez, Raul P., et al.
Publicado: (2024)
por: Pelaez, Raul P., et al.
Publicado: (2024)
Geometric Deep Learning for Molecular Crystal Structure Prediction
por: Kilgour, Michael, et al.
Publicado: (2023)
por: Kilgour, Michael, et al.
Publicado: (2023)
Artificial Intelligence for Direct Prediction of Molecular Dynamics Across Chemical Space
por: Ge, Fuchun, et al.
Publicado: (2025)
por: Ge, Fuchun, et al.
Publicado: (2025)
A Reinforcement Learning-Driven Transformer GAN for Molecular Generation
por: Li, Chen, et al.
Publicado: (2025)
por: Li, Chen, et al.
Publicado: (2025)
Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks
por: Thiemann, Fabian L., et al.
Publicado: (2025)
por: Thiemann, Fabian L., et al.
Publicado: (2025)
Consistent Sampling and Simulation: Molecular Dynamics with Energy-Based Diffusion Models
por: Plainer, Michael, et al.
Publicado: (2025)
por: Plainer, Michael, et al.
Publicado: (2025)
Advancing Molecular Machine Learning Representations with Stereoelectronics-Infused Molecular Graphs
por: Boiko, Daniil A., et al.
Publicado: (2024)
por: Boiko, Daniil A., et al.
Publicado: (2024)
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations
por: Schopmans, Henrik, et al.
Publicado: (2024)
por: Schopmans, Henrik, et al.
Publicado: (2024)
Martignac: Computational workflows for reproducible, traceable, and composable coarse-grained Martini simulations
por: Bereau, Tristan, et al.
Publicado: (2024)
por: Bereau, Tristan, et al.
Publicado: (2024)
Molecular Machine Learning in Chemical Process Design
por: Rittig, Jan G., et al.
Publicado: (2025)
por: Rittig, Jan G., et al.
Publicado: (2025)
MUBen: Benchmarking the Uncertainty of Molecular Representation Models
por: Li, Yinghao, et al.
Publicado: (2023)
por: Li, Yinghao, et al.
Publicado: (2023)
React-OT: Optimal Transport for Generating Transition State in Chemical Reactions
por: Duan, Chenru, et al.
Publicado: (2024)
por: Duan, Chenru, et al.
Publicado: (2024)
Navigating Chemical Space with Latent Flows
por: Wei, Guanghao, et al.
Publicado: (2024)
por: Wei, Guanghao, et al.
Publicado: (2024)
ELECTRA: A Cartesian Network for 3D Charge Density Prediction with Floating Orbitals
por: Elsborg, Jonas, et al.
Publicado: (2025)
por: Elsborg, Jonas, et al.
Publicado: (2025)
A Descriptor Is All You Need: Accurate Machine Learning of Nonadiabatic Coupling Vectors
por: Martinka, Jakub, et al.
Publicado: (2025)
por: Martinka, Jakub, et al.
Publicado: (2025)
Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems
por: Scherbela, Michael, et al.
Publicado: (2025)
por: Scherbela, Michael, et al.
Publicado: (2025)
Are neural scaling laws leading quantum chemistry astray?
por: Lee, Siwoo, et al.
Publicado: (2025)
por: Lee, Siwoo, et al.
Publicado: (2025)
High-performance training and inference for deep equivariant interatomic potentials
por: Tan, Chuin Wei, et al.
Publicado: (2025)
por: Tan, Chuin Wei, et al.
Publicado: (2025)
Ejemplares similares
-
Adversarial reverse mapping of condensed-phase molecular structures: Chemical transferability
por: Stieffenhofer, Marc, et al.
Publicado: (2021) -
Navigating Chemical Space: Multi-Level Bayesian Optimization with Hierarchical Coarse-Graining
por: Walter, Luis J., et al.
Publicado: (2025) -
Energy-Based Coarse-Graining in Molecular Dynamics: A Flow-Based Framework without Data
por: Stupp, Maximilian, et al.
Publicado: (2025) -
Fokker-Planck Score Learning: Efficient Free-Energy Estimation under Periodic Boundary Conditions
por: Nagel, Daniel, et al.
Publicado: (2025) -
Data-Efficient Multidimensional Free Energy Estimation via Physics-Informed Score Learning
por: Nagel, Daniel, et al.
Publicado: (2026)