{"total":32,"rows":[{"id":"2202.08516","title":"SAITS: Self-Attention-based Imputation for Time Series","created":"2022-02-17","cited_by_count":169,"area":null},{"id":"2102.03657","title":"Neural SDEs as Infinite-Dimensional GANs","created":"2021-02-06","cited_by_count":161,"area":null},{"id":"2111.11344","title":"Modeling Irregular Time Series with Continuous Recurrent Units","created":"2021-11-22","cited_by_count":103,"area":null},{"id":"2105.13493","title":"Efficient and Accurate Gradients for Neural SDEs","created":"2021-05-27","cited_by_count":71,"area":null},{"id":"2103.12413","title":"Neural ODE Processes","created":"2021-03-23","cited_by_count":57,"area":null},{"id":"2210.02040","title":"GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks","created":"2022-10-05","cited_by_count":44,"area":null},{"id":"2211.02590","title":"Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion","created":"2022-11-04","cited_by_count":39,"area":null},{"id":"2305.16274","title":"Non-adversarial training of Neural SDEs with signature kernel scores","created":"2023-05-25","cited_by_count":37,"area":null},{"id":"2309.03755","title":"TSGBench: Time Series Generation Benchmark","created":"2023-09-07","cited_by_count":26,"area":null},{"id":"2310.15290","title":"Reliable Generation of Privacy-preserving Synthetic Electronic Health Record Time Series via Diffusion Models","created":"2023-10-23","cited_by_count":24,"area":null},{"id":"2112.06823","title":"Multi-Asset Spot and Option Market Simulation","created":"2021-12-13","cited_by_count":17,"area":null},{"id":"2106.15580","title":"Continuous Latent Process Flows","created":"2021-06-29","cited_by_count":10,"area":null},{"id":"2203.08588","title":"MIMO-GAN: Generative MIMO Channel Modeling","created":"2022-03-16","cited_by_count":9,"area":null},{"id":"2309.09222","title":"Bayesian Gaussian Process ODEs via Double Normalizing Flows","created":"2023-09-17","cited_by_count":7,"area":null},{"id":"2406.15747","title":"Modeling Unknown Stochastic Dynamical System Subject to External Excitation","created":"2024-06-22","cited_by_count":7,"area":null},{"id":"2201.00960","title":"Neural Piecewise-Constant Delay Differential Equations","created":"2022-01-04","cited_by_count":4,"area":null},{"id":"2110.06021","title":"Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling","created":"2021-10-12","cited_by_count":3,"area":null},{"id":"2301.08951","title":"Time-Conditioned Generative Modeling of Object-Centric Representations for Video Decomposition and Prediction","created":"2023-01-21","cited_by_count":3,"area":null},{"id":"2406.06518","title":"Data Augmentation for Multivariate Time Series Classification: An Experimental Study","created":"2024-06-10","cited_by_count":3,"area":null},{"id":"2410.04703","title":"Neural Fourier Modelling: A Highly Compact Approach to Time-Series Analysis","created":"2024-10-07","cited_by_count":3,"area":null},{"id":"2508.02758","title":"CTBench: Cryptocurrency Time Series Generation Benchmark","created":"2025-08-03","cited_by_count":3,"area":null},{"id":"2512.10401","title":"Diffusion differentiable resampling","created":"2025-12-11","cited_by_count":2,"area":null},{"id":"2402.06293","title":"Probabilistic Forecasting of Irregular Time Series via Conditional Flows","created":"2024-02-09","cited_by_count":1,"area":null},{"id":"2507.14467","title":"Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network","created":"2025-07-19","cited_by_count":1,"area":null},{"id":"2208.07333","title":"Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles","created":"2022-08-15","cited_by_count":0,"area":null},{"id":"2209.00173","title":"Continuous-time Particle Filtering for Latent Stochastic Differential Equations","created":"2022-09-01","cited_by_count":0,"area":null},{"id":"2304.13131","title":"Directed Chain Generative Adversarial Networks","created":"2023-04-25","cited_by_count":0,"area":null},{"id":"2306.17797","title":"HIDFlowNet: A Flow-Based Deep Network for Hyperspectral Image Denoising","created":"2023-06-20","cited_by_count":0,"area":null},{"id":"2312.14698","title":"Time-changed normalizing flows for accurate SDE modeling","created":"2023-12-22","cited_by_count":0,"area":null},{"id":"2406.07246","title":"Marginalization Consistent Probabilistic Forecasting of Irregular Time Series via Mixture of Separable flows","created":"2024-06-11","cited_by_count":0,"area":null},{"id":"2601.04279","title":"Generation of synthetic delay time series for air transport applications","created":"2026-01-07","cited_by_count":0,"area":null},{"id":"2607.10026","title":"Robustly Invertible Nonlinear Dynamics and the BiLipREN: From Inversion-Based Control to Generative Trajectory Modelling","created":"2026-07-10","cited_by_count":0,"area":null}],"next_cursor":null}