sequential data

Disentangled Recurrent Wasserstein Autoencoder ICLR 2021 Distribution Regression for Sequential Data AISTATS 2021 Online Variational Filtering and Parameter Learning NeurIPS 2021 Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections ICLR 2021 SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data ICML 2021 Understanding Recurrent Neural Networks Using Nonequilibrium Response Theory JMLR 2021 An efficient representation of chronological events in medical texts EMNLP 2020 Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances ICML 2020 Context Aware Sequence Modeling IJCAI 2020 COT-GAN: Generating Sequential Data via Causal Optimal Transport NeurIPS 2020 Disentangled Representations for Sequence Data using Information Bottleneck Principle ACML 2020 Explainable Inference on Sequential Data via Memory-Tracking IJCAI 2020 Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions ICML 2020 Introducing Probabilistic Bézier Curves for N-Step Sequence Prediction AAAI 2020 Learning Agent Representations for Ice Hockey NeurIPS 2020 Online Positive and Unlabeled Learning IJCAI 2020 Particle Filter Recurrent Neural Networks AAAI 2020 S3VAE: Self-Supervised Sequential VAE for Representation Disentanglement and Data Generation CVPR 2020 Switching Poisson Gamma Dynamical Systems IJCAI 2020 Variational Inference for Sequential Data with Future Likelihood Estimates ICML 2020 Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation AAAI 2020 Adversarial Dropout for Recurrent Neural Networks AAAI 2019 A Neural Turn-Taking Model without RNN Interspeech 2019 Can SGD Learn Recurrent Neural Networks with Provable Generalization? NeurIPS 2019 Generalized Tensor Models for Recurrent Neural Networks ICLR 2019