Time Series

How to Predict Seawater Temperature for Sustainable Marine Aquaculture (Student Abstract) AAAI 2020 Tweedie-Hawkes Processes: Interpreting the Phenomena of Outbreaks AAAI 2020 Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting NeurIPS 2019 Time-series Generative Adversarial Networks NeurIPS 2019 Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling ICLR 2019 Deconvolutional Time Series Regression: A Technique for Modeling Temporally Diffuse Effects EMNLP 2018 Deep Poisson gamma dynamical systems NeurIPS 2018 End-to-End Time Series Imputation via Residual Short Paths ACML 2018 Infinite-Horizon Gaussian Processes NeurIPS 2018 Safe Active Learning for Time-Series Modeling with Gaussian Processes NeurIPS 2018 Bayesian Intermittent Demand Forecasting for Large Inventories NeurIPS 2016 Correcting Forecasts with Multifactor Neural Attention ICML 2016 A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure NeurIPS 2015 High-dimensional neural spike train analysis with generalized count linear dynamical systems NeurIPS 2015 Rate-Agnostic (Causal) Structure Learning NeurIPS 2015 Fast Kernel Learning for Multidimensional Pattern Extrapolation NeurIPS 2014 Stochastic variational inference for hidden Markov models NeurIPS 2014 Variational Gaussian Process State-Space Models NeurIPS 2014 Causal Inference on Time Series using Restricted Structural Equation Models NeurIPS 2013 Inferring neural population dynamics from multiple partial recordings of the same neural circuit NeurIPS 2013 Recurrent linear models of simultaneously-recorded neural populations NeurIPS 2013 Training and Analysing Deep Recurrent Neural Networks NeurIPS 2013 Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting NeurIPS 2012 Expectation Propagation in Gaussian Process Dynamical Systems NeurIPS 2012 A Model for Temporal Dependencies in Event Streams NeurIPS 2011