Saved in:
| Main Authors: | Wang, Zifan, Harting, Alice, Barreau, Matthieu, Zavlanos, Michael M., Johansson, Karl H. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.14807 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Closed-Loop Neural Operator-Based Observer of Traffic Density
by: Harting, Alice, et al.
Published: (2025)
by: Harting, Alice, et al.
Published: (2025)
Federated Flow Matching
by: Wang, Zifan, et al.
Published: (2025)
by: Wang, Zifan, et al.
Published: (2025)
Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning
by: Wang, Zifan, et al.
Published: (2026)
by: Wang, Zifan, et al.
Published: (2026)
Distributionally Robust Federated Learning with Outlier Resilience
by: Wang, Zifan, et al.
Published: (2025)
by: Wang, Zifan, et al.
Published: (2025)
Wasserstein Distributionally Robust Nash Equilibrium Seeking with Heterogeneous Data: A Lagrangian Approach
by: Wang, Zifan, et al.
Published: (2025)
by: Wang, Zifan, et al.
Published: (2025)
Risk-averse Learning with Non-Stationary Distributions
by: Wang, Siyi, et al.
Published: (2024)
by: Wang, Siyi, et al.
Published: (2024)
Group Distributionally Robust Machine Learning under Group Level Distributional Uncertainty
by: Konti, Xenia, et al.
Published: (2025)
by: Konti, Xenia, et al.
Published: (2025)
Iterative Training of Physics-Informed Neural Networks with Fourier-enhanced Features
by: Wu, Yulun, et al.
Published: (2025)
by: Wu, Yulun, et al.
Published: (2025)
Online Traffic Density Estimation using Physics-Informed Neural Networks
by: Wilkman, Dennis, et al.
Published: (2025)
by: Wilkman, Dennis, et al.
Published: (2025)
KKL Observer Synthesis for Nonlinear Systems via Physics-Informed Learning
by: Niazi, M. Umar B., et al.
Published: (2025)
by: Niazi, M. Umar B., et al.
Published: (2025)
Risk-Averse Learning with Varying Risk Levels
by: Wang, Siyi, et al.
Published: (2025)
by: Wang, Siyi, et al.
Published: (2025)
A Control Perspective on Training PINNs
by: Barreau, Matthieu, et al.
Published: (2025)
by: Barreau, Matthieu, et al.
Published: (2025)
(Un)supervised Learning of Maximal Lyapunov Functions
by: Barreau, Matthieu, et al.
Published: (2024)
by: Barreau, Matthieu, et al.
Published: (2024)
Curriculum-Learned Vanishing Stacked Residual PINNs for Hyperbolic PDE State Reconstruction
by: Eshkofti, Katayoun, et al.
Published: (2026)
by: Eshkofti, Katayoun, et al.
Published: (2026)
First- and Zeroth-Order Learning in Asynchronous Games
by: Wang, Zifan, et al.
Published: (2025)
by: Wang, Zifan, et al.
Published: (2025)
Learning of Nash Equilibria in Risk-Averse Games
by: Wang, Zifan, et al.
Published: (2024)
by: Wang, Zifan, et al.
Published: (2024)
Risk-averse learning with delayed feedback
by: Wang, Siyi, et al.
Published: (2024)
by: Wang, Siyi, et al.
Published: (2024)
MILP initialization for solving parabolic PDEs with PINNs
by: Li, Sirui, et al.
Published: (2025)
by: Li, Sirui, et al.
Published: (2025)
Wasserstein Distributionally Robust Policy Evaluation and Learning for Contextual Bandits
by: Shen, Yi, et al.
Published: (2023)
by: Shen, Yi, et al.
Published: (2023)
Projected Gradient Descent for Constrained Decision-Dependent Optimization
by: Wang, Zifan, et al.
Published: (2025)
by: Wang, Zifan, et al.
Published: (2025)
Asymmetric Feedback Learning in Online Convex Games
by: Wang, Zifan, et al.
Published: (2023)
by: Wang, Zifan, et al.
Published: (2023)
Path Signatures and Graph Neural Networks for Slow Earthquake Analysis: Better Together?
by: Riess, Hans, et al.
Published: (2024)
by: Riess, Hans, et al.
Published: (2024)
Distributionally Robust Clustered Federated Learning: A Case Study in Healthcare
by: Konti, Xenia, et al.
Published: (2024)
by: Konti, Xenia, et al.
Published: (2024)
Data-Driven vs Traditional Approaches to Power Transformer's Top-Oil Temperature Estimation
by: Tembo, Francis, et al.
Published: (2025)
by: Tembo, Francis, et al.
Published: (2025)
Flow Matching Guide and Code
by: Lipman, Yaron, et al.
Published: (2024)
by: Lipman, Yaron, et al.
Published: (2024)
Weighted Conditional Flow Matching
by: Calvo-Ordonez, Sergio, et al.
Published: (2025)
by: Calvo-Ordonez, Sergio, et al.
Published: (2025)
Optimal Sensor Placement in Power Transformers Using Physics-Informed Neural Networks
by: Li, Sirui, et al.
Published: (2025)
by: Li, Sirui, et al.
Published: (2025)
Policy Evaluation in Distributional LQR (Extended Version)
by: Wang, Zifan, et al.
Published: (2023)
by: Wang, Zifan, et al.
Published: (2023)
Follow the Mean: Reference-Guided Flow Matching
by: Curvo, Pedro M. P., et al.
Published: (2026)
by: Curvo, Pedro M. P., et al.
Published: (2026)
Control Synthesis from Linear Temporal Logic Specifications using Model-Free Reinforcement Learning
by: Bozkurt, Alper Kamil, et al.
Published: (2019)
by: Bozkurt, Alper Kamil, et al.
Published: (2019)
FairPOT: Balancing AUC Performance and Fairness with Proportional Optimal Transport
by: Liu, Pengxi, et al.
Published: (2025)
by: Liu, Pengxi, et al.
Published: (2025)
D-Flow SGLD: Source-Space Posterior Sampling for Scientific Inverse Problems with Flow Matching
by: Parikh, Meet Hemant, et al.
Published: (2026)
by: Parikh, Meet Hemant, et al.
Published: (2026)
Advantage-Guided Diffusion for Model-Based Reinforcement Learning
by: Foffano, Daniele, et al.
Published: (2026)
by: Foffano, Daniele, et al.
Published: (2026)
Energy Guided Geometric Flow Matching
by: Zweig, Aaron, et al.
Published: (2025)
by: Zweig, Aaron, et al.
Published: (2025)
Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
by: Liu, Guangyi, et al.
Published: (2025)
by: Liu, Guangyi, et al.
Published: (2025)
Training Free Guided Flow Matching with Optimal Control
by: Wang, Luran, et al.
Published: (2024)
by: Wang, Luran, et al.
Published: (2024)
Correcting Source Mismatch in Flow Matching with Radial-Angular Transport
by: Oubari, Fouad, et al.
Published: (2026)
by: Oubari, Fouad, et al.
Published: (2026)
Learning Optimal Strategies for Temporal Tasks in Stochastic Games
by: Bozkurt, Alper Kamil, et al.
Published: (2021)
by: Bozkurt, Alper Kamil, et al.
Published: (2021)
Path-Guided Flow Matching for Dataset Distillation
by: Li, Xuhui, et al.
Published: (2026)
by: Li, Xuhui, et al.
Published: (2026)
Transfer Reinforcement Learning in Heterogeneous Action Spaces using Subgoal Mapping
by: Sivakumar, Kavinayan P., et al.
Published: (2024)
by: Sivakumar, Kavinayan P., et al.
Published: (2024)
Similar Items
-
Closed-Loop Neural Operator-Based Observer of Traffic Density
by: Harting, Alice, et al.
Published: (2025) -
Federated Flow Matching
by: Wang, Zifan, et al.
Published: (2025) -
Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning
by: Wang, Zifan, et al.
Published: (2026) -
Distributionally Robust Federated Learning with Outlier Resilience
by: Wang, Zifan, et al.
Published: (2025) -
Wasserstein Distributionally Robust Nash Equilibrium Seeking with Heterogeneous Data: A Lagrangian Approach
by: Wang, Zifan, et al.
Published: (2025)