Gasthaus, Jan

17 publications

AISTATS 2022 Learning Quantile Functions Without Quantile Crossing for Distribution-Free Time Series Forecasting Youngsuk Park, Danielle Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang

AISTATS 2022 Multivariate Quantile Function Forecaster Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus

IJCAI 2022 Neural Contextual Anomaly Detection for Time Series Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert, Jan Gasthaus

NeurIPS 2022 On the Detrimental Effect of Invariances in the Likelihood for Variational Inference Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus

ICLR 2022 PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Shubham Kapoor, Rajbir Singh Nirwan, Valentin Flunkert, Jan Gasthaus, Tim Januschowski

NeurIPS 2021 Detecting Anomalous Event Sequences with Temporal Point Processes Oleksandr Shchur, Ali Caner Turkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann

ICML 2021 End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series Syama Sundar Rangapuram, Lucien D Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski

NeurIPS 2021 Probabilistic Forecasting: A Level-Set Approach Hilaf Hasson, Bernie Wang, Tim Januschowski, Jan Gasthaus

NeurIPS 2020 Deep Rao-Blackwellised Particle Filters for Time Series Forecasting Richard Kurle, Syama Sundar Rangapuram, Emmanuel de Bézenac, Stephan Günnemann, Jan Gasthaus

MLOSS 2020 GluonTS: Probabilistic and Neural Time Series Modeling in Python Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang

ICML 2019 Deep Factors for Forecasting Yuyang Wang, Alex Smola, Danielle Maddix, Jan Gasthaus, Dean Foster, Tim Januschowski

NeurIPS 2019 High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus

AISTATS 2019 Probabilistic Forecasting with Spline Quantile Function RNNs Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski

NeurIPS 2018 Deep State Space Models for Time Series Forecasting Syama Sundar Rangapuram, Matthias W Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, Tim Januschowski

NeurIPS 2010 Improvements to the Sequence Memoizer Jan Gasthaus, Yee W. Teh

ICML 2009 A Stochastic Memoizer for Sequence Data Frank D. Wood, Cédric Archambeau, Jan Gasthaus, Lancelot James, Yee Whye Teh

NeurIPS 2008 Dependent Dirichlet Process Spike Sorting Jan Gasthaus, Frank Wood, Dilan Gorur, Yee W. Teh