Saved in:
| Main Authors: | Yi, Yinzhuang, Cortés, Jorge, Atanasov, Nikolay |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.04007 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Constrained Variational Inference via Safe Particle Flow
by: Yi, Yinzhuang, et al.
Published: (2025)
by: Yi, Yinzhuang, et al.
Published: (2025)
Distributionally Robust Lyapunov Function Search Under Uncertainty
by: Long, Kehan, et al.
Published: (2022)
by: Long, Kehan, et al.
Published: (2022)
Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions
by: Long, Kehan, et al.
Published: (2025)
by: Long, Kehan, et al.
Published: (2025)
Distributionally Robust Policy and Lyapunov-Certificate Learning
by: Long, Kehan, et al.
Published: (2024)
by: Long, Kehan, et al.
Published: (2024)
Sensor-Based Distributionally Robust Control for Safe Robot Navigation in Dynamic Environments
by: Long, Kehan, et al.
Published: (2024)
by: Long, Kehan, et al.
Published: (2024)
EAST: Environment Aware Safe Tracking using Planning and Control Co-Design
by: Li, Zhichao, et al.
Published: (2023)
by: Li, Zhichao, et al.
Published: (2023)
Distributed Multi-Agent Reinforcement Learning with One-hop Neighbors and Compute Straggler Mitigation
by: Wang, Baoqian, et al.
Published: (2022)
by: Wang, Baoqian, et al.
Published: (2022)
Rainbow-DemoRL: Combining Improvements in Demonstration-Augmented Reinforcement Learning
by: Bhatt, Dwait, et al.
Published: (2026)
by: Bhatt, Dwait, et al.
Published: (2026)
Distributed Bayesian Estimation in Sensor Networks: Consensus on Marginal Densities
by: Paritosh, Parth, et al.
Published: (2023)
by: Paritosh, Parth, et al.
Published: (2023)
Safe Control of Second-Order Systems with Linear Constraints
by: Alyaseen, Mohammed, et al.
Published: (2025)
by: Alyaseen, Mohammed, et al.
Published: (2025)
Safety-Critical Control of Discontinuous Systems with Nonsmooth Safe Sets
by: Alyaseen, Mohammed, et al.
Published: (2024)
by: Alyaseen, Mohammed, et al.
Published: (2024)
Maxitive Donsker-Varadhan Formulation for Possibilistic Variational Inference
by: Singh, Jasraj, et al.
Published: (2025)
by: Singh, Jasraj, et al.
Published: (2025)
Neural Configuration-Space Barriers for Manipulation Planning and Control
by: Long, Kehan, et al.
Published: (2025)
by: Long, Kehan, et al.
Published: (2025)
Particle Semi-Implicit Variational Inference
by: Lim, Jen Ning, et al.
Published: (2024)
by: Lim, Jen Ning, et al.
Published: (2024)
Particle-based Energetic Variational Inference
by: Wang, Yiwei, et al.
Published: (2020)
by: Wang, Yiwei, et al.
Published: (2020)
Pawsterior: Variational Flow Matching for Structured Simulation-Based Inference
by: Carrasco-Pollo, Jorge, et al.
Published: (2026)
by: Carrasco-Pollo, Jorge, et al.
Published: (2026)
How Feature Learning Can Improve Neural Scaling Laws
by: Bordelon, Blake, et al.
Published: (2024)
by: Bordelon, Blake, et al.
Published: (2024)
A Dynamical Model of Neural Scaling Laws
by: Bordelon, Blake, et al.
Published: (2024)
by: Bordelon, Blake, et al.
Published: (2024)
The Optimization Landscape of SGD Across the Feature Learning Strength
by: Atanasov, Alexander, et al.
Published: (2024)
by: Atanasov, Alexander, et al.
Published: (2024)
ARD-VAE: A Statistical Formulation to Find the Relevant Latent Dimensions of Variational Autoencoders
by: Saha, Surojit, et al.
Published: (2025)
by: Saha, Surojit, et al.
Published: (2025)
On Generalization for Generative Flow Networks
by: Krichel, Anas, et al.
Published: (2024)
by: Krichel, Anas, et al.
Published: (2024)
Variational Inference via Smoothed Particle Hydrodynamics
by: Huang, Yongchao
Published: (2024)
by: Huang, Yongchao
Published: (2024)
Variational Flow Matching for Graph Generation
by: Eijkelboom, Floor, et al.
Published: (2024)
by: Eijkelboom, Floor, et al.
Published: (2024)
Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference
by: Nguyen, Dai Hai, et al.
Published: (2023)
by: Nguyen, Dai Hai, et al.
Published: (2023)
Variational Flow Models: Flowing in Your Style
by: Do, Kien, et al.
Published: (2024)
by: Do, Kien, et al.
Published: (2024)
Feasibility Analysis and Regularity Characterization of Distributionally Robust Safe Stabilizing Controllers
by: Mestres, Pol, et al.
Published: (2023)
by: Mestres, Pol, et al.
Published: (2023)
Importance Sampling With Stochastic Particle Flow and Diffusion Optimization
by: Zhang, Wenyu, et al.
Published: (2024)
by: Zhang, Wenyu, et al.
Published: (2024)
Variational Pseudo Marginal Methods for Jet Reconstruction in Particle Physics
by: Yang, Hanming, et al.
Published: (2024)
by: Yang, Hanming, et al.
Published: (2024)
Mixed Variational Flows for Discrete Variables
by: Diluvi, Gian Carlo, et al.
Published: (2023)
by: Diluvi, Gian Carlo, et al.
Published: (2023)
Variational Bayesian Flow Network for Graph Generation
by: Xiong, Yida, et al.
Published: (2026)
by: Xiong, Yida, et al.
Published: (2026)
Bernstein Flows for Flexible Posteriors in Variational Bayes
by: Dürr, Oliver, et al.
Published: (2022)
by: Dürr, Oliver, et al.
Published: (2022)
Narrative Consolidation: Formulating a New Task for Unifying Multi-Perspective Accounts
by: Finger, Roger A., et al.
Published: (2025)
by: Finger, Roger A., et al.
Published: (2025)
Risk and cross validation in ridge regression with correlated samples
by: Atanasov, Alexander, et al.
Published: (2024)
by: Atanasov, Alexander, et al.
Published: (2024)
Scaling and renormalization in high-dimensional regression
by: Atanasov, Alexander, et al.
Published: (2024)
by: Atanasov, Alexander, et al.
Published: (2024)
FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering
by: Qin, Juehang, et al.
Published: (2025)
by: Qin, Juehang, et al.
Published: (2025)
Koopman Subspace Pruning in Reproducing Kernel Hilbert Spaces via Principal Vectors
by: Shah, Dhruv, et al.
Published: (2026)
by: Shah, Dhruv, et al.
Published: (2026)
Finite-Particle Rates for Regularized Stein Variational Gradient Descent
by: He, Ye, et al.
Published: (2026)
by: He, Ye, et al.
Published: (2026)
Transformer as an Euler Discretization of Score-based Variational Flow
by: Liao, Huadong
Published: (2026)
by: Liao, Huadong
Published: (2026)
Normalizing Flow-based Differentiable Particle Filters
by: Chen, Xiongjie, et al.
Published: (2024)
by: Chen, Xiongjie, et al.
Published: (2024)
Hierarchical Forecast Reconciliation on Networks: A Network Flow Optimization Formulation
by: Sharma, Charupriya, et al.
Published: (2025)
by: Sharma, Charupriya, et al.
Published: (2025)
Similar Items
-
Constrained Variational Inference via Safe Particle Flow
by: Yi, Yinzhuang, et al.
Published: (2025) -
Distributionally Robust Lyapunov Function Search Under Uncertainty
by: Long, Kehan, et al.
Published: (2022) -
Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions
by: Long, Kehan, et al.
Published: (2025) -
Distributionally Robust Policy and Lyapunov-Certificate Learning
by: Long, Kehan, et al.
Published: (2024) -
Sensor-Based Distributionally Robust Control for Safe Robot Navigation in Dynamic Environments
by: Long, Kehan, et al.
Published: (2024)