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EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting., , , , , , , и . WWW, стр. 3102-3112. ACM, (2022)GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks., , , , и . NeurIPS, (2022)Linear, or Non-Linear, That is the Question!, , , , , , и . WSDM, стр. 517-525. ACM, (2022)LightMove: A Lightweight Next-POI Recommendation forTaxicab Rooftop Advertising., , , , , , и . CIKM, стр. 3857-3866. ACM, (2021)OCT-GAN: Neural ODE-based Conditional Tabular GANs., , , , и . WWW, стр. 1506-1515. ACM / IW3C2, (2021)Large-Scale Flight Frequency Optimization with Global Convergence in the US Domestic Air Passenger Markets., , , , , , , и . SDM, стр. 711-719. SIAM, (2021)ACE-NODE: Attentive Co-Evolving Neural Ordinary Differential Equations., , , , и . KDD, стр. 736-745. ACM, (2021)Invertible Tabular GANs: Killing Two Birds with One Stone for Tabular Data Synthesis., , , , и . NeurIPS, стр. 4263-4273. (2021)Operator-learning-inspired Modeling of Neural Ordinary Differential Equations., , , , , , , , и . CoRR, (2023)Operator-Learning-Inspired Modeling of Neural Ordinary Differential Equations., , , , , , , , и . AAAI, стр. 11543-11551. AAAI Press, (2024)