ChargeFlow: Flow-Matching Refinement of Charge-Conditioned Electron Densities
Fuente:
arXiv
Guardado en:
| Autores principales: | Nguyen, Tri Minh, Tawfik, Sherif Abdulkader, Tran, Truyen, Venkatesh, Svetha |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks
por: Nguyen, Tri Minh, et al.
Publicado: (2024)
por: Nguyen, Tri Minh, et al.
Publicado: (2024)
Embedding material graphs using the electron-ion potential: application to material fracture
por: Tawfik, Sherif Abdulkader, et al.
Publicado: (2024)
por: Tawfik, Sherif Abdulkader, et al.
Publicado: (2024)
Score-based Integrated Gradient for Root Cause Explanations of Outliers
por: Nguyen, Phuoc, et al.
Publicado: (2026)
por: Nguyen, Phuoc, et al.
Publicado: (2026)
Enhancing Length Extrapolation in Sequential Models with Pointer-Augmented Neural Memory
por: Le, Hung, et al.
Publicado: (2024)
por: Le, Hung, et al.
Publicado: (2024)
MolCrystalFlow: Molecular Crystal Structure Prediction via Flow Matching
por: Zeng, Cheng, et al.
Publicado: (2026)
por: Zeng, Cheng, et al.
Publicado: (2026)
DMFlow: Disordered Materials Generation by Flow Matching
por: Wu, Liming, et al.
Publicado: (2026)
por: Wu, Liming, et al.
Publicado: (2026)
Generating Symmetric Materials using Latent Flow Matching
por: Karmush, Anmar, et al.
Publicado: (2026)
por: Karmush, Anmar, et al.
Publicado: (2026)
Finding the Trigger: Causal Abductive Reasoning on Video Events
por: Le, Thao Minh, et al.
Publicado: (2025)
por: Le, Thao Minh, et al.
Publicado: (2025)
Learning Structural Causal Models from Ordering: Identifiable Flow Models
por: Le, Minh Khoa, et al.
Publicado: (2024)
por: Le, Minh Khoa, et al.
Publicado: (2024)
Higher-Order Equivariant Neural Networks for Charge Density Prediction in Materials
por: Koker, Teddy, et al.
Publicado: (2023)
por: Koker, Teddy, et al.
Publicado: (2023)
FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions
por: Sriram, Anuroop, et al.
Publicado: (2024)
por: Sriram, Anuroop, et al.
Publicado: (2024)
FlowMM: Generating Materials with Riemannian Flow Matching
por: Miller, Benjamin Kurt, et al.
Publicado: (2024)
por: Miller, Benjamin Kurt, et al.
Publicado: (2024)
MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks
por: Kim, Nayoung, et al.
Publicado: (2024)
por: Kim, Nayoung, et al.
Publicado: (2024)
Variable-Agnostic Causal Exploration for Reinforcement Learning
por: Nguyen, Minh Hoang, et al.
Publicado: (2024)
por: Nguyen, Minh Hoang, et al.
Publicado: (2024)
Flow Matching for Accelerated Simulation of Atomic Transport in Crystalline Materials
por: Nam, Juno, et al.
Publicado: (2024)
por: Nam, Juno, et al.
Publicado: (2024)
Revisiting the Dataset Bias Problem from a Statistical Perspective
por: Do, Kien, et al.
Publicado: (2024)
por: Do, Kien, et al.
Publicado: (2024)
Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink
por: Elsborg, Jonas, et al.
Publicado: (2026)
por: Elsborg, Jonas, et al.
Publicado: (2026)
Symmetry-Aware Bayesian Flow Networks for Crystal Generation
por: Ruple, Laura, et al.
Publicado: (2025)
por: Ruple, Laura, et al.
Publicado: (2025)
Equivariant Machine Learning Interatomic Potentials with Global Charge Redistribution
por: Maruf, Moin Uddin, et al.
Publicado: (2025)
por: Maruf, Moin Uddin, et al.
Publicado: (2025)
Property-Guided Molecular Generation and Optimization via Latent Flows
por: Lobo, Alexander Arjun, et al.
Publicado: (2026)
por: Lobo, Alexander Arjun, et al.
Publicado: (2026)
Hierarchy-Guided Topology Latent Flow for Molecular Graph Generation
por: Awasthi, Urvi, et al.
Publicado: (2026)
por: Awasthi, Urvi, et al.
Publicado: (2026)
Continual Fine-Tuning of Large Language Models via Program Memory
por: Le, Hung, et al.
Publicado: (2026)
por: Le, Hung, et al.
Publicado: (2026)
OrgFlow: Generative Modeling of Organic Crystal Structures from Molecular Graphs
por: Vahediahmar, Mohammadmahdi, et al.
Publicado: (2026)
por: Vahediahmar, Mohammadmahdi, et al.
Publicado: (2026)
Bayesian Optimistic Optimisation with Exponentially Decaying Regret
por: Tran-The, Hung, et al.
Publicado: (2021)
por: Tran-The, Hung, et al.
Publicado: (2021)
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization
por: Tran-The, Hung, et al.
Publicado: (2019)
por: Tran-The, Hung, et al.
Publicado: (2019)
Continual Safety Alignment via Gradient-Based Sample Selection
por: Bach, Thong, et al.
Publicado: (2026)
por: Bach, Thong, et al.
Publicado: (2026)
Rethinking Deep Alignment Through The Lens Of Incomplete Learning
por: Bach, Thong, et al.
Publicado: (2025)
por: Bach, Thong, et al.
Publicado: (2025)
Accelerating Electronic Stopping Power Predictions by 10 Million Times with a Combination of Time-Dependent Density Functional Theory and Machine Learning
por: Ward, Logan, et al.
Publicado: (2023)
por: Ward, Logan, et al.
Publicado: (2023)
Beyond Surprise: Improving Exploration Through Surprise Novelty
por: Le, Hung, et al.
Publicado: (2023)
por: Le, Hung, et al.
Publicado: (2023)
Reasoning Under 1 Billion: Memory-Augmented Reinforcement Learning for Large Language Models
por: Le, Hung, et al.
Publicado: (2025)
por: Le, Hung, et al.
Publicado: (2025)
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization
por: Tran-The, Hung, et al.
Publicado: (2022)
por: Tran-The, Hung, et al.
Publicado: (2022)
End-to-End Analysis of Charge Stability Diagrams with Transformers
por: Marchand, Rahul, et al.
Publicado: (2025)
por: Marchand, Rahul, et al.
Publicado: (2025)
Conditional Variable Flow Matching: Transforming Conditional Densities with Amortized Conditional Optimal Transport
por: Generale, Adam P., et al.
Publicado: (2024)
por: Generale, Adam P., et al.
Publicado: (2024)
Uncertainty-Guided Checkpoint Selection for Reinforcement Finetuning of Large Language Models
por: Nguyen, Manh, et al.
Publicado: (2025)
por: Nguyen, Manh, et al.
Publicado: (2025)
Curvature-Aware Safety Restoration In LLMs Fine-Tuning
por: Bach, Thong, et al.
Publicado: (2025)
por: Bach, Thong, et al.
Publicado: (2025)
SPaCe: Unlocking Sample-Efficient Large Language Models Training With Self-Pace Curriculum Learning
por: Do, Dai, et al.
Publicado: (2025)
por: Do, Dai, et al.
Publicado: (2025)
FlowRefiner: Flow Matching-Based Iterative Refinement for 3D Turbulent Flow Simulation
por: Dai, Yilong, et al.
Publicado: (2026)
por: Dai, Yilong, et al.
Publicado: (2026)
Physics Aware Representation Learning on Electronic Charge Density for Materials Property Prediction
por: Kumar, Kammampati Sai, et al.
Publicado: (2026)
por: Kumar, Kammampati Sai, et al.
Publicado: (2026)
Machine Learning for Improved Density Functional Theory Thermodynamics
por: Simak, Sergei I., et al.
Publicado: (2025)
por: Simak, Sergei I., et al.
Publicado: (2025)
Physically-Constrained Autoencoder-Assisted Bayesian Optimization for Refinement of High-Dimensional Defect-Sensitive Single Crystalline Structure
por: Agada, Joseph Oche, et al.
Publicado: (2025)
por: Agada, Joseph Oche, et al.
Publicado: (2025)
Ejemplares similares
-
Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks
por: Nguyen, Tri Minh, et al.
Publicado: (2024) -
Embedding material graphs using the electron-ion potential: application to material fracture
por: Tawfik, Sherif Abdulkader, et al.
Publicado: (2024) -
Score-based Integrated Gradient for Root Cause Explanations of Outliers
por: Nguyen, Phuoc, et al.
Publicado: (2026) -
Enhancing Length Extrapolation in Sequential Models with Pointer-Augmented Neural Memory
por: Le, Hung, et al.
Publicado: (2024) -
MolCrystalFlow: Molecular Crystal Structure Prediction via Flow Matching
por: Zeng, Cheng, et al.
Publicado: (2026)