Stochastic Differential Equations

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Period ending 2026-09-21

8 new papers

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Period ending 2026-09-14

10 new papers

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Period ending 2026-09-07

3 new papers

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252 papers

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  1. A Blueprint for Equilibrium-Based Differentiable Continuous-Variable Thermodynamic Computing

    Jul 17, 2026Owen Lockwood, Jérémy Béjanin, Joost Bus +4ThermodynamicsIn-Memory Computing

  2. A Semiparametric Framework for Stochastic Fundamental Diagram Modeling

    Jul 17, 2026Pengnan Chi, Xiaoliang Ma, Magnus Jansson +1Stochastic SystemsTraffic

  3. NeuralChaos: Optimal Adapted Approximation of Square Integrable Predictable Processes

    Jul 15, 2026Anastasis Kratsios, Giulia Livieri, Philipp SchmockerNeural-Network ApproximationStochastic Systems

  4. LatentFlow: A General Framework for Conditioning Stochastic Processes

    Jul 14, 2026Louis Sharrock, Lachlan Astfalck, Henry MossStochastic SystemsGenerative Flow Networks

  5. AutoPath: Learning Transferable Goal-Conditioned Stochastic Path Prior for Safe Navigation Without Human Demonstrations

    Jul 13, 2026Ziyang Zhang, Boyang Zhou, Zesong Yang +8Object Goal NavigationNavigation

  6. Sticky Jump Diffusions: A Unifying View of Masked, Continuous, and Hybrid Diffusion

    Jul 12, 2026Pascal Jutras-Dubé, Patrick Pynadath, Jeremy Lu +2Stochastic Differential Equations

  7. Diachronic Sample Integration: Robust Tail-Risk Estimation with Generative Models

    Jul 12, 2026Shuning Zhao, Patrick Wong, Leran Zhang +1Long-Tailed DistributionStochastic Differential Equations

  8. From Stochastic to Stable: Rank Stability and Structural Sufficiency in AI Visibility Measurement

    Jul 11, 2026Ronald SielinskiCitationsVisibility

  9. How much Data do We Need? Sequential Data Collection for Stochastic Programming

    Jul 11, 2026Xin Li, Juergen Branke, Xuan Vinh DoanOptimal StoppingStochastic Optimization

  10. Solving Stochastic Fixed-Point Equations with High Probability

    Jul 10, 2026Jelena DiakonikolasFixed-Point IterationVariance Reduction

  11. Deep Learning Method for Stationary Distribution of Reflected Brownian Motion

    Jul 9, 2026Jim Dai, Zhanhao ZhangStochastic Differential EquationsLoss Function

  12. Tensor Train Diffusion: Leveraging Low-Rank Structures for High-Dimensional Score-Based Sampling

    Jul 7, 2026Robert Gruhlke, Julius Berner, David Sommer +1Diffusion SamplingStochastic Differential Equations

  13. Mixture-of-Gaussians-Guided Schedule Design for Brownian Bridge Diffusion Models

    Jul 3, 2026Ron Levi, Michael EladSchrödinger BridgesImage Restoration

  14. PedNStream: Scalable Network Flow Simulation for Pedestrian Traffic Management

    Jul 1, 2026Weiming Mai, Dorine Duives, Serge HoogendoornMicroscopic Traffic SimulationsClosed-Loop Reliability

  15. Introduction to Stochastic Differential Equations for Generative Machine Learning: A Variational Perspective

    Jun 30, 2026Ole Winther, Paul Jeha, Sander Dieleman +3Stochastic Differential EquationsFokker--Planck Equation

  16. Non-parametric recovery of causal diffusion mechanisms from steady-state observations

    Jun 29, 2026Richard Schwank, Mathias DrtonStochastic Differential EquationsCausal Graph

  17. A Distributionally Robust Framework for Learned Reconstructions in Inverse Problems

    Jun 29, 2026Floor van Maarschalkerwaart, Subhadip Mukherjee, Christoph Brune +1Ill-Posed Inverse ProblemInverse Problem

  18. Stabilizing Extrapolation in Looped Transformers via Learned Stochastic Stopping

    Jun 29, 2026Hsun-Yu Kuo, El Mahdi Chayti, Patrik Reizinger +2Early StoppingStochastic

  19. RainODE: Continuous-Time Precipitation Forecasting with Latent Neural ODEs

    Jun 29, 2026Yeeun Seong, Doyi Kim, Minseok Seo +1PrecipitationSpatio-Temporal Forecasting

  20. Analyzing Uncertainty in the Spatial Representation of the Kinematic Bicycle Model

    Jun 28, 2026Shafayat Abrar, M. Zaeem Baig, Shahir Ul Islam Anzal +1OdometryVehicle Dynamics

  21. A Posteriori Error Analysis for Decoupled Neural Approximations of Fully Coupled FBSDEs with Control Mismatch

    Jun 28, 2026Xichuan ZhangStochastic Differential EquationsNeural-Network Approximation

  22. Fractional Stochastic Neural Networks

    Jun 28, 2026Yuecai Han, Jianming XuStochastic Differential EquationsStochastic Optimal Control

  23. Analysis of Adam Algorithms for Stochastic Dynamic Systems

    Jun 27, 2026Xin Zheng, Yifei Jin, Lei GuoAdamStochastic Dynamics

  24. Brownian Bridge Diffusion-Based Joint Channel Estimation and Data Detection for Jamming-Resilient Receivers

    Jun 27, 2026Honghan She, Yufan Cheng, Tieming Sun +3Jamming AttacksJoint Channel Estimation

  25. Disentangling Continuous-Time Latent Dynamics: Identifiability of Latent SDEs via Diffusion Shifts

    Jun 26, 2026Yuanyuan Wang, Wenjie Wang, Haoxuan Li +2IdentifiabilityCausal Representation Learning

  26. Prob-BBDM: a Probabilistic Brownian Bridge Diffusion Model for MRI sequence image-to-image translation

    Jun 23, 2026Martin Valls, Pascal Bourdon, Christine Fernandez-Maloigne +2Image-To-Image TranslationMagnetic Resonance Imaging

  27. Deep numerical schemes for systems of Ergodic BSDEs with applications to regime-switching forward utilities

    Jun 23, 2026Guillaume Broux-Quemerais, Sarah Kaakai, Anis Matoussi +1Stochastic Differential EquationsClassical Numerical Solver

  28. An Open-Source LFSR-Based Stochastic Leaky Integrate-and-Fire Neuron in SkyWater 130 nm: Design, Stochastic Characterisation, and Rate Coding

    Jun 22, 2026Poornima Kumaresan, Santhosh SivasubramaniNeuromorphic HardwareAnd Mixed-Signal Circuits

  29. The Origins of Stochasticity: Comprehensive Investigations on Uncertainty Quantification for Large Language Models

    Jun 22, 2026Xiang-Jun Ou, Shuang Liang, Xin-Yu Hu +3Large Language Model UncertaintyReliable Uncertainty Quantification

  30. Delta-Diffusion: Modeling Longitudinal Brain Amyloid-PET Trajectories via Conditional Poisson Diffusion Bridge

    Jun 20, 2026Yongheng Sun, Minhui Yu, Mengqi Wu +2Positron Emission TomographyDiffusion Dynamics

  31. Neural Architecture Distributions: A New Paradigm for Stochastic Segmentation

    Jun 19, 2026Conghui Li, Junhao Huang, Chern Hong Lim +2Distributional LearningIdentity-Conditioned Latent Diffusion Models

  32. Stochastic Signed Distance Processes

    Jun 18, 2026Hiroki Sakuma, Masatoshi OkutomiGeometry-Aware Ray CastingVolume

  33. Score Approximation for Diffusion Models on Arbitrary Low-Dimensional Structures

    Jun 18, 2026Xinhe Mu, Zaijiu Shang, Zhaoqi Zhou +4Score-Based Diffusion ModelLow-Dimensional Structure

  34. pdSTL: Probabilistic Differentiable Signal Temporal Logic for Stochastic Systems

    Jun 17, 2026Bennett Dogbey, Hemanth ManjunathaSignal Temporal LogicInductive Logic Programming

  35. Anomaly Detection for Sparse and Irregular Multivariate Time Series with Latent SDEs

    Jun 17, 2026Martin Uray, Dominik Geng, Florian Graf +2Time-Series Anomaly DetectionAnomaly Detection

  36. Finite-Time Queue Peak Laws in Stochastic Networks: Logarithmic Scaling After Geometric Thresholds

    Jun 16, 2026Hao Liang, Cheng Tang, Yunzong XuStochastic DelaysOptimal Scheduling

  37. A Diffusion Approximation for Temporal-Difference Learning with Linear Features under Markovian Noise

    Jun 16, 2026M. Forzo, E. Monzio Compagnoni, A. Russo +1Temporal DifferenceStochastic Approximation

  38. Escape from Delusional Echo Trap: Symmetry Breaking, Stochastic Dynamics and Mathematical Mitigation Strategies for Algorithmic Sycophancy

    Jun 16, 2026Sayantari Ghosh, Saumik Bhattacharya, Partha Pratim ChakrabartiSycophancyBelief

  39. Latent space mapping of interpretable structural coordinates from stochastic single-molecule signals

    Jun 15, 2026Matteo Cartiglia, Sandro Kuppel, Wouter Botermans Wannes Peeters +7Multimodal Physiological SignalsMolecular Structure Elucidation

  40. Diffusion Flow Matching: Dimension-Improved KL Bounds and Wasserstein Guarantees

    Jun 15, 2026Marta Gentiloni Silveri, Giovanni Conforti, Alain DurmusWasserstein Gradient FlowsGenerative Models

  41. Graphical conditional generative modeling for digital twin modeling

    Jun 15, 2026Zongren Zou, Théo Bourdais, Ricardo Baptista +1Surrogate ModelsGenerative Models

  42. Closing the Approximation Gap in Simulation-free Latent SDEs

    Jun 15, 2026Henry D. Smith, Brian L. Trippe, Scott W. LindermanStochastic Differential EquationsVariational Inference

  43. Noise-Driven Instrument Based on Coherent Quantum and Stochastic Oscillator Models

    Jun 14, 2026Felipe Gonzalez de la Maza, Maciej Lewenstein, Antoine Reserbat-Plantey +1InstrumentMusic Generation

  44. Brownian Kernel Ladders

    Jun 14, 2026Mahdi Mohammadigohari, Giuseppe Di Fatta, Giuseppe Nicosia +1Kernel Hilbert SpacesStochastic Differential Equations

  45. Generative modelling powered by room-temperature polariton condensates

    Jun 13, 2026Yuan Wang, Marcin Muszynski, Avinash Dash +3Generative Adversarial NetworkGenerative Models

  46. Temporal Difference Learning for Diffusion Models

    Jun 13, 2026Qizhen Ying, Yangchen Pan, Victor Adrian Prisacariu +1Denoising TrajectoryGenerative Models

  47. Deep Spectral Learning of Embedded Latent Transfer Operators for Stochastic Dynamical Systems

    Jun 12, 2026Ryogo Tanaka, Yoshinobu KawaharaLatent DynamicsStochastic Dynamics

  48. Accelerating Speculative Diffusions via Block Verification

    Jun 11, 2026Alexander Soen, Hisham Husain, Valentin De Bortoli +1Diffusion Language ModelsSpeculative Decoding

  49. Fast-SDE: Efficient Single-Microphone Sound Source Distance Estimation in Reverberant Environments

    Jun 10, 2026Jiang Wang, Runwu Shi, Yaozhong Kang +3Sound Source LocalizationDirection-Of-Arrival Estimation

  50. Itô maps for any-step SDEs

    Jun 9, 2026Zhengkai Pan, Peter Potaptchik, Wenxi Yao +2Invertible FlowsStochastic Differential Equations

  51. First-Order Trajectory Matching: Fast Ensemble Predictions of Chaotic, Turbulent, Stochastic Systems

    Jun 9, 2026Shreya Jha, Timo Schorlepp, Nicholas Geissler +2Stochastic DynamicsStochastic Systems

  52. One Step Closer to Ground Truth: A Multi-Scale Residual-Aware Representation Learning Pipeline for Predicting Time Series Data

    Jun 9, 2026Amrijit Biswas, Mustafa Kamal, Robin Krambroeckers +4Spatio-Temporal TransformersTime Series

  53. LAFP: Preserving Latent Action Structure in Latent Policy Learning via Flow Matching

    Jun 9, 2026Jiexi Lyu, Xizhou Bu, Qingqiu Huang +4Latent ActionsHierarchical Flow Matching

  54. Dropout-GRPO: Variational Stochasticity for Continuous Latent Reasoning

    Jun 8, 2026Wooil JungEfficient Latent ReasoningGroup Relative Policy Optimization

  55. Operator learning for solving Fokker-Planck equations with various initial conditions

    Jun 8, 2026Li Zeng, Xiaoliang Wan, Yaobin Wang +2Fokker--Planck EquationStochastic Dynamics

  56. The Token Not Taken: Sampling, State, and the Stochasticity of AI Agents

    Jun 8, 2026Muhammad Zia Hydari, Raja IqbalArtificial Intelligence AgentsStochastic

  57. DisPOSE: Projected Polystochastic Diffusion for Self-Supervised Multi-View 3D Human Pose Estimation

    Jun 5, 2026Tony Danjun Wang, Tolga Birdal, Nassir Navab +13D Pose EstimatorAvatar Reconstruction

  58. Covariance Shrinkage via Stochastic Interpolation

    Jun 5, 2026Mathieu Chalvidal, Florentin Coeurdoux, Eric Vanden-EijndenCovariance EstimationEmpirical Risk Minimization

  59. Residual-Controlled Multiplier Learning for Stochastic Constrained Decision-Making

    Jun 5, 2026Kang Liu, Jianchen Hu, Ziyu Qu +3Feedback LinearizationMini-Batch Stochastic Gradient Descent

  60. Capturing non-Markovian dynamics in non-equilibrium stochastic systems using flow matching

    Jun 4, 2026Bhargav Sriram Siddani, John B. Bell, Alejandro L. Garcia +1Stochastic Differential EquationsPhysical Dynamics