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Time Series

48 papers

Papers per year

4
5
'20
'25

Papers

Detecting Anomalous Event Sequences with Temporal Point Processes NIPS 2021
DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales NIPS 2021
Deep Switching Auto-Regressive Factorization: Application to Time Series Forecasting AAAI 2021
Attentive Neural Point Processes for Event Forecasting AAAI 2021
Fairness in Forecasting and Learning Linear Dynamical Systems AAAI 2021
Spatiotemporal Graph Neural Network for Performance Prediction of Photovoltaic Power Systems AAAI 2021
Predictive Agent-Based Modeling of Natural Disasters Using Machine Learning AAAI 2021
Forecasting Irreversible Disease via Progression Learning CVPR 2021
Deep Rao-Blackwellised Particle Filters for Time Series Forecasting NIPS 2020
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting NIPS 2020
Tweedie-Hawkes Processes: Interpreting the Phenomena of Outbreaks AAAI 2020
How to Predict Seawater Temperature for Sustainable Marine Aquaculture (Student Abstract) AAAI 2020
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting NIPS 2019
Time-series Generative Adversarial Networks NIPS 2019
Deep Poisson gamma dynamical systems NIPS 2018
Safe Active Learning for Time-Series Modeling with Gaussian Processes NIPS 2018
Infinite-Horizon Gaussian Processes NIPS 2018
Deconvolutional Time Series Regression: A Technique for Modeling Temporally Diffuse Effects EMNLP 2018
Bayesian Intermittent Demand Forecasting for Large Inventories NIPS 2016
Correcting Forecasts with Multifactor Neural Attention ICML 2016
Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting NIPS 2012
A Model for Temporal Dependencies in Event Streams NIPS 2011
Non-stationary continuous dynamic Bayesian networks NIPS 2009