Energy Generative Modeling: A Lyapunov-based Energy Matching Perspective
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Yixuan, Xue, Wenqian, Dixon, Warren E. |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Riemannian Lyapunov Optimizer: A Unified Framework for Optimization
by: Wang, Yixuan, et al.
Published: (2026)
by: Wang, Yixuan, et al.
Published: (2026)
Lyapunov-Based Kolmogorov-Arnold Network (KAN) Adaptive Control
by: Shen, Xuehui, et al.
Published: (2025)
by: Shen, Xuehui, et al.
Published: (2025)
Effective Model Pruning: Measure The Redundancy of Model Components
by: Wang, Yixuan, et al.
Published: (2025)
by: Wang, Yixuan, et al.
Published: (2025)
Goal inference with Rao-Blackwellized Particle Filters
by: Wang, Yixuan, et al.
Published: (2025)
by: Wang, Yixuan, et al.
Published: (2025)
Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling
by: Balcerak, Michal, et al.
Published: (2025)
by: Balcerak, Michal, et al.
Published: (2025)
A Kinetic Energy Perspective of Flow Matching
by: Li, Ziyun, et al.
Published: (2026)
by: Li, Ziyun, et al.
Published: (2026)
System Identification and Control Using Lyapunov-Based Deep Neural Networks without Persistent Excitation: A Concurrent Learning Approach
by: Hart, Rebecca G., et al.
Published: (2025)
by: Hart, Rebecca G., et al.
Published: (2025)
Graph Energy Matching: Transport-Aligned Energy-Based Modeling for Graph Generation
by: Balcerak, Michal, et al.
Published: (2026)
by: Balcerak, Michal, et al.
Published: (2026)
Lyapunov-based Adaptive Transformer (LyAT) for Control of Stochastic Nonlinear Systems
by: Akbari, Saiedeh, et al.
Published: (2025)
by: Akbari, Saiedeh, et al.
Published: (2025)
Equilibrium Matching: Generative Modeling with Implicit Energy-Based Models
by: Wang, Runqian, et al.
Published: (2025)
by: Wang, Runqian, et al.
Published: (2025)
Structure-Preserving Physics-Informed Neural Networks With Energy or Lyapunov Structure
by: Chu, Haoyu, et al.
Published: (2024)
by: Chu, Haoyu, et al.
Published: (2024)
Energy-Based Flow Matching for Generating 3D Molecular Structure
by: Zhou, Wenyin, et al.
Published: (2025)
by: Zhou, Wenyin, et al.
Published: (2025)
Iterated Energy-based Flow Matching for Sampling from Boltzmann Densities
by: Woo, Dongyeop, et al.
Published: (2024)
by: Woo, Dongyeop, et al.
Published: (2024)
Incorporating Inductive Biases to Energy-based Generative Models
by: Li, Yukun, et al.
Published: (2025)
by: Li, Yukun, et al.
Published: (2025)
A Diffusive Classification Loss for Learning Energy-based Generative Models
by: OuYang, RuiKang, et al.
Published: (2026)
by: OuYang, RuiKang, et al.
Published: (2026)
Matching Features, Not Tokens: Energy-Based Fine-Tuning of Language Models
by: Jelassi, Samy, et al.
Published: (2026)
by: Jelassi, Samy, et al.
Published: (2026)
Joint Learning of Energy-based Models and their Partition Function
by: Sander, Michael E., et al.
Published: (2025)
by: Sander, Michael E., et al.
Published: (2025)
Energy Guided Geometric Flow Matching
by: Zweig, Aaron, et al.
Published: (2025)
by: Zweig, Aaron, et al.
Published: (2025)
EnfoPath: Energy-Informed Analysis of Generative Trajectories in Flow Matching
by: Li, Ziyun, et al.
Published: (2025)
by: Li, Ziyun, et al.
Published: (2025)
Energy-Weighted Flow Matching for Offline Reinforcement Learning
by: Zhang, Shiyuan, et al.
Published: (2025)
by: Zhang, Shiyuan, et al.
Published: (2025)
Learning Energy-Based Generative Models via Potential Flow: A Variational Principle Approach to Probability Density Homotopy Matching
by: Loo, Junn Yong, et al.
Published: (2025)
by: Loo, Junn Yong, et al.
Published: (2025)
Free Energy Surface Sampling via Reduced Flow Matching
by: Liu, Zichen, et al.
Published: (2026)
by: Liu, Zichen, et al.
Published: (2026)
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities
by: Akhound-Sadegh, Tara, et al.
Published: (2024)
by: Akhound-Sadegh, Tara, et al.
Published: (2024)
Energy-Guided Generative Modeling for Low-Energy Molecular Structure Discovery
by: Xu, Guikun, et al.
Published: (2025)
by: Xu, Guikun, et al.
Published: (2025)
Score Matching for Estimating Finite Point Processes
by: Cao, Haoqun, et al.
Published: (2025)
by: Cao, Haoqun, et al.
Published: (2025)
Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization
by: Zhou, Xiangxin, et al.
Published: (2024)
by: Zhou, Xiangxin, et al.
Published: (2024)
Contrastive Self-Supervised Learning at the Edge: An Energy Perspective
by: Famá, Fernanda, et al.
Published: (2025)
by: Famá, Fernanda, et al.
Published: (2025)
Data Imputation from the Perspective of Graph Dirichlet Energy
by: Zhang, Weiqi, et al.
Published: (2023)
by: Zhang, Weiqi, et al.
Published: (2023)
Kolmogorov-Arnold Energy Models: Fast, Interpretable Generative Modeling
by: Raj, Prithvi
Published: (2025)
by: Raj, Prithvi
Published: (2025)
Generating Physically Consistent Molecules with Energy-Based Models
by: Griesbacher, Christoph, et al.
Published: (2026)
by: Griesbacher, Christoph, et al.
Published: (2026)
Bridging OOD Detection and Generalization: A Graph-Theoretic View
by: Wang, Han, et al.
Published: (2024)
by: Wang, Han, et al.
Published: (2024)
Neural Thermodynamic Integration: Free Energies from Energy-based Diffusion Models
by: Máté, Bálint, et al.
Published: (2024)
by: Máté, Bálint, et al.
Published: (2024)
Langevin Dynamics: A Unified Perspective on Optimization via Lyapunov Potentials
by: Chen, August Y., et al.
Published: (2024)
by: Chen, August Y., et al.
Published: (2024)
THOR: A Generic Energy Estimation Approach for On-Device Training
by: Zhang, Jiaru, et al.
Published: (2025)
by: Zhang, Jiaru, et al.
Published: (2025)
EnergyDiff: Universal Time-Series Energy Data Generation using Diffusion Models
by: Lin, Nan, et al.
Published: (2024)
by: Lin, Nan, et al.
Published: (2024)
Potential Score Matching: Debiasing Molecular Structure Sampling with Potential Energy Guidance
by: Guo, Liya, et al.
Published: (2025)
by: Guo, Liya, et al.
Published: (2025)
Energy-based Autoregressive Generation for Neural Population Dynamics
by: Ge, Ningling, et al.
Published: (2025)
by: Ge, Ningling, et al.
Published: (2025)
Potential Energy based Mixture Model for Noisy Label Learning
by: Wang, Zijia, et al.
Published: (2024)
by: Wang, Zijia, et al.
Published: (2024)
The Energy Loss Phenomenon in RLHF: A New Perspective on Mitigating Reward Hacking
by: Miao, Yuchun, et al.
Published: (2025)
by: Miao, Yuchun, et al.
Published: (2025)
Chance-constrained Flow Matching for High-Fidelity Constraint-aware Generation
by: Liang, Jinhao, et al.
Published: (2025)
by: Liang, Jinhao, et al.
Published: (2025)
Similar Items
-
Riemannian Lyapunov Optimizer: A Unified Framework for Optimization
by: Wang, Yixuan, et al.
Published: (2026) -
Lyapunov-Based Kolmogorov-Arnold Network (KAN) Adaptive Control
by: Shen, Xuehui, et al.
Published: (2025) -
Effective Model Pruning: Measure The Redundancy of Model Components
by: Wang, Yixuan, et al.
Published: (2025) -
Goal inference with Rao-Blackwellized Particle Filters
by: Wang, Yixuan, et al.
Published: (2025) -
Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling
by: Balcerak, Michal, et al.
Published: (2025)