{"total":45,"rows":[{"id":"2303.08797","title":"Stochastic Interpolants: A Unifying Framework for Flows and Diffusions","created":"2023-03-15","cited_by_count":939,"area":null},{"id":"2110.11291","title":"Likelihood Training of Schr\\\"odinger Bridge using Forward-Backward SDEs Theory","created":"2021-10-21","cited_by_count":219,"area":null},{"id":"2206.04642","title":"Probability flow solution of the Fokker-Planck equation","created":"2022-06-09","cited_by_count":47,"area":null},{"id":"2212.14424","title":"Normalizing flow neural networks by JKO scheme","created":"2022-12-29","cited_by_count":39,"area":null},{"id":"2208.00638","title":"Composable Text Controls in Latent Space with ODEs","created":"2022-08-01","cited_by_count":28,"area":null},{"id":"2304.13534","title":"A mean-field games laboratory for generative modeling","created":"2023-04-26","cited_by_count":28,"area":null},{"id":"2102.06350","title":"Projected Wasserstein gradient descent for high-dimensional Bayesian inference","created":"2021-02-12","cited_by_count":24,"area":null},{"id":"2310.07216","title":"Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes","created":"2023-10-11","cited_by_count":21,"area":null},{"id":"2310.03597","title":"Sampling via Gradient Flows in the Space of Probability Measures","created":"2023-10-05","cited_by_count":20,"area":null},{"id":"2302.11024","title":"Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance","created":"2023-02-21","cited_by_count":16,"area":null},{"id":"2409.01464","title":"Stein transport for Bayesian inference","created":"2024-09-02","cited_by_count":11,"area":null},{"id":"2205.14240","title":"Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference","created":"2022-05-27","cited_by_count":10,"area":null},{"id":"2403.04493","title":"What makes an image realistic?","created":"2024-03-07","cited_by_count":10,"area":null},{"id":"2301.13636","title":"Transport with Support: Data-Conditional Diffusion Bridges","created":"2023-01-31","cited_by_count":9,"area":null},{"id":"2410.07501","title":"Inferring biological processes with intrinsic noise from cross-sectional data","created":"2024-10-10","cited_by_count":9,"area":null},{"id":"2104.03384","title":"Ensemble Inference Methods for Models With Noisy and Expensive Likelihoods","created":"2021-04-07","cited_by_count":8,"area":null},{"id":"2210.17230","title":"Lipschitz-regularized gradient flows and generative particle algorithms for high-dimensional scarce data","created":"2022-10-31","cited_by_count":8,"area":null},{"id":"2305.15577","title":"Minimizing $f$-Divergences by Interpolating Velocity Fields","created":"2023-05-24","cited_by_count":8,"area":null},{"id":"2412.03312","title":"Path-Guided Particle-based Sampling","created":"2024-12-04","cited_by_count":8,"area":null},{"id":"2308.14945","title":"Noise-Free Sampling Algorithms via Regularized Wasserstein Proximals","created":"2023-08-28","cited_by_count":7,"area":null},{"id":"2504.07793","title":"Revisiting Likelihood-Based Out-of-Distribution Detection by Modeling Representations","created":"2025-04-10","cited_by_count":6,"area":null},{"id":"2511.05924","title":"DiScoFormer: Plug-In Density and Score Estimation with Transformers","created":"2025-11-08","cited_by_count":6,"area":null},{"id":"2110.02787","title":"Relative Entropy Gradient Sampler for Unnormalized Distributions","created":"2021-10-06","cited_by_count":5,"area":null},{"id":"2310.02366","title":"Stochastic force inference via density estimation","created":"2023-10-03","cited_by_count":5,"area":null},{"id":"2405.09536","title":"Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning","created":"2024-05-15","cited_by_count":4,"area":null},{"id":"2405.10392","title":"Transport based particle methods for the Fokker-Planck-Landau equation","created":"2024-05-16","cited_by_count":4,"area":null},{"id":"2504.18130","title":"Score-based deterministic density sampling","created":"2025-04-25","cited_by_count":4,"area":null},{"id":"2401.04372","title":"Stable generative modeling using Schr\\\"odinger bridges","created":"2024-01-09","cited_by_count":3,"area":null},{"id":"2409.07968","title":"Localized Schr\\\"odinger Bridge Sampler","created":"2024-09-12","cited_by_count":3,"area":null},{"id":"2505.12097","title":"Proximal optimal transport divergences","created":"2025-05-17","cited_by_count":3,"area":null},{"id":"2603.12057","title":"Adaptive Weighted h-Transform Sampling for Coarse-Guided Visual Generation","created":"2026-03-12","cited_by_count":3,"area":null},{"id":"2301.08102","title":"Geometric path augmentation for inference of sparsely observed stochastic nonlinear systems","created":"2023-01-19","cited_by_count":1,"area":null},{"id":"2304.00423","title":"Geometric constraints improve inference of sparsely observed stochastic dynamics","created":"2023-04-02","cited_by_count":1,"area":null},{"id":"2602.05227","title":"Radon--Wasserstein Gradient Flows for Interacting-Particle Sampling in High Dimensions","created":"2026-02-05","cited_by_count":1,"area":null},{"id":"2606.11138","title":"First-Order Trajectory Matching: Fast Ensemble Predictions of Chaotic, Turbulent, Stochastic Systems","created":"2026-06-09","cited_by_count":1,"area":null},{"id":"2606.27192","title":"LISA: Likelihood Score Alignment for Visual-condition Controllable Generation","created":"2026-06-25","cited_by_count":1,"area":null},{"id":"2608.29107","title":"PathGuide: Dynamic Classifier-Free Guidance via On-Policy Transport Alignment","created":"2026-08-29","cited_by_count":1,"area":null},{"id":"2310.00745","title":"Deterministic Langevin Unconstrained Optimization with Normalizing Flows","created":"2023-10-01","cited_by_count":0,"area":null},{"id":"2401.13530","title":"Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space","created":"2024-01-24","cited_by_count":0,"area":null},{"id":"2504.03158","title":"Accelerating Particle-based Energetic Variational Inference","created":"2025-04-04","cited_by_count":0,"area":null},{"id":"2510.16656","title":"Simulation-free Structure Learning for Stochastic Population Dynamics","created":"2025-10-18","cited_by_count":0,"area":null},{"id":"2604.25137","title":"Quantum Dynamics via Score Matching on Bohmian Trajectories","created":"2026-04-28","cited_by_count":0,"area":null},{"id":"2605.09685","title":"Learning Unified Representations of Normalcy for Time Series Anomaly Detection","created":"2026-05-10","cited_by_count":0,"area":null},{"id":"2605.16486","title":"StAD: Stein Amortized Divergence for Fast Likelihoods with Diffusion and Flow","created":"2026-05-15","cited_by_count":0,"area":null},{"id":"2609.35060","title":"Beyond Gradient Flow: Identifiability and Recovery from Distribution Snapshots","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}