Wasserstein Gradient Flows

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Online Gradient Computation for Warping Gaussian Process Transformations
Sep 15, 2026Emilio Ruiz-Moreno, Konstantinos Slavakis, Baltasar Beferull-LozanoGaussian Process Wasserstein Gradient Flows
How I learned to stop worrying and love StopGrads: Stationarity, Convergence, and a case study on Flow Map Learning
Sep 14, 2026Max W. Shen, Mark Goldstein, Zichu Wang +2Wasserstein Gradient Flows
Learning Informative Prior with Infinite-Dimensional Continuous Normalizing Flow for Bayesian Inverse Problem
Sep 3, 2026Yang Zhao, Junxiong Jia, Tao ZhouIll-Posed Inverse Problem Normalizing Flows
On the Reliability of Generative Augmentation: A Wasserstein-Based Theoretical and Empirical Study
Sep 1, 2026Chathurika S Abeykoon, Mathias Nthiani Muia, Mallory GoldsteinData Augmentation Extreme Class Imbalance
Reciprocity Separates Gradient Flow from Rotation in Conservative Physical Learning
Aug 31, 2026Ruiwu Niu, Xiaowen Bi, Michaël Antonie van WykWasserstein Gradient Flows Closed-Loop Performance
Estimating Population-Risk Curves Along Nonconvex Gradient Flows from the Training Sample
Aug 31, 2026Mingzhi SongConvex Loss Wasserstein Gradient Flows
Reward-guided Fine-Tuning of One-Step Generative Models via Wasserstein Gradient Flow
Aug 30, 2026Hoseong Hwang, Woorim Han, Joungin Chun +2Wasserstein Gradient Flows Reward Gradients
Fine-Tuning Generative Models for Extreme Events via CVaR-Penalized Wasserstein Gradient Flows
Aug 12, 2026Thejani Gamage, Hyemin Gu, Zhizhen Zhang +3Heavy-Tailed Noise Wasserstein Gradient Flows
Quotient Dynamics, Effective Curvature, and Implicit Bias in Positive Quadratic Networks
Jul 28, 2026Pengcheng ChengSpectral Descent Local Curvature
Guarantees by Construction for Learned Finite Volume Schemes on Steady Supersonic Flow
Jul 22, 2026Denis GueyffierTurbulence Wasserstein Gradient Flows
TCAM-Diff: Triplane-Aware Cross-Attention Medical Diffusion Model
Jul 15, 2026Zhenkai Zhang, Krista A. Ehinger, Tom Drummond3D Latent Diffusion Model Medical Image Generation
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs
Jul 15, 2026Mohammad ForouheshIll-Posed Inverse Problem Regularization Methods
Score Accuracy Along the Forward Diffusion Does Not Certify Numerical Stability in Diffusion Sampling
Jul 9, 2026Yiwei ZhouDiffusion Sampling Wasserstein Gradient Flows
The Map Behind the Flow: Finite-Step Gradient Descent as a Dynamical System
Jul 6, 2026Thomas HofmannGradient Descent Wasserstein Gradient Flows
Wasserstein Residuals: Learning Gradient Flows from Population Dynamics
Jul 6, 2026Markus Heinonen, Yair Shenfeld, Ricardo Baptista +4Wasserstein Gradient Flows Wasserstein Distance
Generative wave propagator
Jul 5, 2026Shijun Cheng, Tariq AlkhalifahWave Seismic Interpretation
The Geometry Behind Diffusion and Flow Matching: Gradient Flows and Geodesics in Wasserstein Space
Jun 23, 2026Yian Yao, Weiwei ZhangWasserstein Gradient Flows Wasserstein Distance
Generative Robust Optimisation
Jun 21, 2026Yuhui Yin, Vassilis M. CharitopoulosPose Uncertainty Multi-Objective Optimization
Dual-Channel Grounded World Modeling (DCGWM): Structural Prevention of Objective Interference Collapse via Heterogeneous External Grounding with Inward-Only Gradient Flow
Jun 17, 2026Akshay HazareWasserstein Gradient Flows Interference
Correcting Sensor-Induced Distribution Drift with Wasserstein Adversarial Learning
Jun 17, 2026Saraa Ali, Vladimir Bocharnikov, Fedor Ratnikov +3Recalibration Distribution Shifts
Mitigating the Contractivity Trap in Diffusion ODEs via Stein Stabilization
Jun 5, 2026Shigui Li, Delu ZengDiffusion Models Wasserstein Gradient Flows
Diffusion Models Observe Only Gradients: A Geometric Perspective on Score Matching Errors
Jun 4, 2026Naïl B. Khelifa, Richard E. Turner, Ramji VenkataramananScore-Based Diffusion Model Diffusion Models
Gradient descent at the Edge of Stability: free energy model and kinetic description of the two-layer network
Jun 3, 2026Antonin Chodron de CourcelGradient Descent Two-Layer Neural Networks
A Unifying View of Variational Generative Wasserstein Flows
May 29, 2026Paul Caucheteux, Clément Bonet, Anna KorbaWasserstein Gradient Flows Wasserstein Distance
Reachability and asymptotics of Gaussian Transformer dynamics
May 29, 2026Albert Alcalde, Zhengping Ji, Enrique ZuazuaCovariance Estimation Wasserstein Gradient Flows
The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer
May 28, 2026Tianhua ChenGenerative Models Generative Artificial Intelligence
Global Convergence of Wasserstein Policy Gradient for Entropy-Regularized Reinforcement Learning
May 25, 2026Zhaoyu Zhu, Rui Gao, Shuang LiPolicy Gradient Kullback-Leibler Regularization
Leveraging Gauge Freedom for Learning Non-Gradient Population Dynamics of Stochastic Systems
May 24, 2026Jules Berman, Tobias Blickhan, Benjamin PeherstorferPopulation Dynamics Wasserstein Gradient Flows
On the Stability of Spherical Hellinger-Kantorovich Flows and Their Implications for Differential Privacy
May 22, 2026Aratrika Mustafi, Soumya MukherjeeDifferential Privacy Wasserstein Gradient Flows
Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer
May 22, 2026Aratrika Mustafi, Soumya Mukherjee, Bharath K. SriperumbudurMuon Wasserstein Gradient Flows
A note on convergence of Wasserstein policy optimization
May 21, 2026David Šiška, Yufei ZhangWasserstein Gradient Flows Optimization Convergence Analysis
Uniform-in-Time Weak Propagation-of-Chaos in Shallow Neural Networks
May 21, 2026Margalit Glasgow, Joan BrunaTwo-Layer Neural Networks Finite Time Analysis
Canonical Regularisation of Wide Feature-Learning Neural Networks
May 18, 2026George Whittle, Pranav Vaidhyanathan, Juliusz Ziomek +2Feature Learning Regularization Methods
Scenario Generation in Roundabouts with Adjustable Interaction Intensity
May 18, 2026Li Li, Till Temmen, Tobias Brinkmann +3Scenario Generation Autonomous Driving
A Unified Framework for Data-Free One-Step Sampling via Wasserstein Gradient Flows
May 18, 2026Chenguang Wang, Tianshu YuWasserstein Gradient Flows Diffusion Sampling
Training Infinitely Deep and Wide Transformers
May 17, 2026Raphaël Barboni, Maarten V. de Hoop, Takashi Furuya +1Wasserstein Gradient Flows Mean-Field Limit
Propagation of Chaos in Contextual Flow Maps
May 16, 2026Shi Chen, Zhengjiang Lin, Kaizhao Liu +1Transformer Variant Wasserstein Gradient Flows
Multi-Headed Transformer Architectures as Time-dependent Wasserstein Gradient Flows
May 15, 2026Alex Massucco, Leonardo Del Grande, Marcello Carioni +2Wasserstein Gradient Flows Diffusion Transformers
Sobolev Regularized MMD Gradient Flow
May 12, 2026Chenyang Tian, Bharath K. Sriperumbudur, Arthur Gretton +1Maximum Mean Discrepancy Wasserstein Gradient Flows
Metric-Gradient Projection for Stable Multi-Agent Policy Learning
May 12, 2026Zuyuan Zhang, Sizhe Tang, Mahdi Imani +1Multi-Agent Reinforcement Learning Wasserstein Gradient Flows
Kernel-Gradient Drifting Models
May 11, 2026Maria Esteban-Casadevall, Jorge Carrasco-Pollo, Max Welling +3Wasserstein Gradient Flows Generative Models
Extended Wasserstein-GAN Approach to Causal Distribution Learning: Density-Free Estimation and Minimax Optimality
May 11, 2026Shu Tamano, Masaaki ImaizumiCausal Inferences Structural Causal Model
Quantitative Local Convergence of Mean-Field Stein Variational Gradient Flow
May 10, 2026Lénaïc Chizat, Maria Colombo, Roberto Colombo +1Wasserstein Gradient Flows Optimization Convergence Analysis
Probability-Flow Distillation: Exact Wasserstein Gradient Flow for High-Fidelity 3D Generation
May 9, 2026Rohith Ramanan, A. N. Rajagopalan3D Latent Diffusion Model Text-To-3D Generation
Consistency Regularised Gradient Flows for Inverse Problems
May 8, 2026Alessio Spagnoletti, Tim Y. J. Wang, Marcelo Pereyra +1Ill-Posed Inverse Problem Inverse Problem
Drifting Field Policy: A One-Step Generative Policy via Wasserstein Gradient Flow
May 8, 2026Juil Koo, Mingue Park, Jiwon Choi +2Diffusion Policies Wasserstein Gradient Flows
Learning Discrete Autoregressive Priors with Wasserstein Gradient Flow
May 7, 2026Bowen Zheng, Yihong Luo, Tianyang HuDiscrete Image Tokenizers Autoregressive Token Prediction
Optimal Confidence Band for Kernel Gradient Flow Estimator
May 7, 2026Yuqian Cheng, Zhuo Chen, Qian LinConfidence Intervals Wasserstein Gradient Flows
Energy Generative Modeling: A Lyapunov-based Energy Matching Perspective
May 7, 2026Yixuan Wang, Wenqian Xue, Warren E. DixonGenerative Models Wasserstein Gradient Flows
On the Wasserstein Gradient Flow Interpretation of Drifting Models
May 6, 2026Arthur Gretton, Li Kevin Wenliang, Alexandre Galashov +3Wasserstein Gradient Flows Generative Models
Finite-Size Gradient Transport in Large Language Model Pretraining: From Cascade Size to Intensive Transport Efficiency
May 3, 2026Ping Wang, Yan-Qi DuLarge Language Model Post-Training Wasserstein Gradient Flows
Diffusion Operator Geometry of Feedforward Representations
May 1, 2026Kanishka ReddyGeometric Machine Learning Feed-Forward
Properties and limitations of geometric tempering for gradient flow dynamics
Apr 22, 2026Francesca Romana Crucinio, Sahani PathirajaWasserstein Gradient Flows Fisher Information
Random Matrix Theory of Early-Stopped Gradient Flow: A Transient BBP Scenario
Apr 20, 2026Florentin Coeurdoux, Grégoire Ferré, Jean-Philippe BouchaudGradient Descent Wasserstein Gradient Flows
Continuous Limits of Coupled Flows in Representation Learning
Apr 18, 2026Zilin Li, Weiwei Xu, Xuchun Tong +2Representation Learning Wasserstein Gradient Flows
Gradient Flow Through Diagram Expansions: Learning Regimes and Explicit Solutions
Feb 4, 2026Dmitry Yarotsky, Eugene Golikov, Yaroslav GusevWasserstein Gradient Flows Tensor
Derivation of effective gradient flow equations and dynamical truncation of training data in Deep Learning
Jan 13, 2025Thomas ChenGradient Descent Wasserstein Gradient Flows
Inclusive KL Gradient Flows: Otto-Wasserstein, Fisher-Rao-Gaussian, and Local-Estimator Dynamics
Oct 31, 2024Jia-Jie ZhuWasserstein Gradient Flows Variational Inference
Fisher-Rao Gradient Flows of Linear Programs and State-Action Natural Policy Gradients
Mar 28, 2024Johannes Müller, Semih Çaycı, Guido MontúfarPolicy Gradient Wasserstein Gradient Flows
A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks
Oct 28, 2022Zhengdao Chen, Eric Vanden-Eijnden, Joan BrunaTwo-Layer Neural Networks Mean-Field Limit

Sep 15, 2026 · cs.LGJ/K move · Enter open · S save

Online Gradient Computation for Warping Gaussian Process Transformations

Emilio Ruiz-Moreno, Konstantinos Slavakis, Baltasar Beferull-Lozano

Warped Gaussian processes (GPs) handle non-Gaussian observations by mapping them into a latent standard GP via a parametric transformation called warping. Existing streaming variants, however, either optimize the warping parameters periodically or sacrifice analytical tractability for a higher model capacity. To bridge this gap, we show that the gradient of the instantaneous negative log-likelihood of a warped GP admits an exact recursive computation. Based on this result, we propose a novel online method for warped GPs that jointly updates the latent GP moments and optimizes the warping parameters.

Gaussian Process Wasserstein Gradient Flows

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