Jan Gasthaus - RankMe

53 papers A* 13A 3B 1Journal 29Unranked 6

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	A Flexible Forecasting Stack. Proc. VLDB Endow. Tim Januschowski, Yuyang Wang, Jan Gasthaus, Syama Sundar Rangapuram, Caner Türkmen, Jasper Zschiegner, Lorenzo Stella, Michael Bohlke-Schneider, Danielle C. Maddix, Konstantinos Benidis, Alexander Alexandrov, Christos Faloutsos, Sebastian Schelter
2023	J	`jnl`	Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. ACM Comput. Surv. Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Yuyang Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, François-Xavier Aubet, Laurent Callot, Tim Januschowski
2023	J	`jnl`	Deep Non-Parametric Time Series Forecaster. CoRR Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski
2022	A*	`conf`	8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications. KDD Sanjay Purushotham, Jun Huan, Cong Shen, Dongjin Song, Yuyang Wang, Jan Gasthaus, Hilaf Hasson, Youngsuk Park, Sungyong Seo, Yuriy Nevmyvaka
2022	J	`jnl`	Criteria for Classifying Forecasting Methods. CoRR Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider, Laurent Callot
2022	J	`jnl`	Diverse Counterfactual Explanations for Anomaly Detection in Time Series. CoRR Déborah Sulem, Michele Donini, Muhammad Bilal Zafar, Francois-Xavier Aubet, Jan Gasthaus, Tim Januschowski, Sanjiv Das, Krishnaram Kenthapadi, Cédric Archambeau
2022	J	`jnl`	Intrinsic Anomaly Detection for Multi-Variate Time Series. CoRR Stephan Rabanser, Tim Januschowski, Kashif Rasul, Oliver Borchert, Richard Kurle, Jan Gasthaus, Michael Bohlke-Schneider, Nicolas Papernot, Valentin Flunkert
2022	A	`conf`	Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting. AISTATS Youngsuk Park, Danielle C. Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang
2022	A	`conf`	Multivariate Quantile Function Forecaster. AISTATS Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus
2022	J	`jnl`	Multivariate Quantile Function Forecaster. CoRR Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus
2022	A*	`conf`	Neural Contextual Anomaly Detection for Time Series. IJCAI Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert, Jan Gasthaus
2022	A*	`conf`	On the detrimental effect of invariances in the likelihood for variational inference. NeurIPS Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
2022	J	`jnl`	On the detrimental effect of invariances in the likelihood for variational inference. CoRR Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
2022	J	`jnl`	Online Time Series Anomaly Detection with State Space Gaussian Processes. CoRR Christian Bock, François-Xavier Aubet, Jan Gasthaus, Andrey Kan, Ming Chen, Laurent Callot
2022	A*	`conf`	PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series. ICLR Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Shubham Kapoor, Rajbir-Singh Nirwan, Valentin Flunkert, Jan Gasthaus, Tim Januschowski
2021	J	`jnl`	A Study of Joint Graph Inference and Forecasting. CoRR Daniel Zügner, François-Xavier Aubet, Victor Garcia Satorras, Tim Januschowski, Stephan Günnemann, Jan Gasthaus
2021	A*	`conf`	Detecting Anomalous Event Sequences with Temporal Point Processes. NeurIPS Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann
2021	J	`jnl`	Detecting Anomalous Event Sequences with Temporal Point Processes. CoRR Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann
2021	A*	`conf`	End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series. ICML Syama Sundar Rangapuram, Lucien D. Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski
2021	J	`jnl`	Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting. CoRR Youngsuk Park, Danielle C. Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang
2021	J	`jnl`	Monte Carlo EM for Deep Time Series Anomaly Detection. CoRR François-Xavier Aubet, Daniel Zügner, Jan Gasthaus
2021	J	`jnl`	Neural Contextual Anomaly Detection for Time Series. CoRR Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert, Jan Gasthaus
2021	J	`jnl`	PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series. CoRR Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Rajbir-Singh Nirwan, Shubham Kapoor, Valentin Flunkert, Jan Gasthaus, Tim Januschowski
2021	A*	`conf`	Probabilistic Forecasting: A Level-Set Approach. NeurIPS Hilaf Hasson, Bernie Wang, Tim Januschowski, Jan Gasthaus
2020	—	`conf`	Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models. ICSOC Workshops Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus
2020	J	`jnl`	Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models. CoRR Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus
2020	A*	`conf`	Deep Rao-Blackwellised Particle Filters for Time Series Forecasting. NeurIPS Richard Kurle, Syama Sundar Rangapuram, Emmanuel de Bézenac, Stephan Günnemann, Jan Gasthaus
2020	—	`conf`	Elastic Machine Learning Algorithms in Amazon SageMaker. SIGMOD Conference Edo Liberty, Zohar S. Karnin, Bing Xiang, Laurence Rouesnel, Baris Coskun, Ramesh Nallapati, Julio Delgado, Amir Sadoughi, Yury Astashonok, Piali Das, Can Balioglu, Saswata Chakravarty, Madhav Jha, Philip Gautier, David Arpin, Tim Januschowski, Valentin Flunkert, Yuyang Wang, Jan Gasthaus, Lorenzo Stella, Syama Sundar Rangapuram, David Salinas, Sebastian Schelter, Alex Smola
2020	—	`conf`	Forecasting Big Time Series: Theory and Practice. WWW (Companion Volume) Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang
2020	J	`jnl`	GluonTS: Probabilistic and Neural Time Series Modeling in Python. J. Mach. Learn. Res. Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Sundar Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang
2020	—	`—`	Hierarchical Bayesian nonparametric models for power-law sequences Jan Gasthaus
2020	J	`jnl`	Neural forecasting: Introduction and literature overview. CoRR Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Bernie Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, Laurent Callot, Tim Januschowski
2020	J	`jnl`	The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models. CoRR Stephan Rabanser, Tim Januschowski, Valentin Flunkert, David Salinas, Jan Gasthaus
2019	—	`conf`	Classical and Contemporary Approaches to Big Time Series Forecasting. SIGMOD Conference Christos Faloutsos, Jan Gasthaus, Tim Januschowski, Yuyang Wang
2019	A*	`conf`	Deep Factors for Forecasting. ICML Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean P. Foster, Tim Januschowski
2019	J	`jnl`	Deep Factors for Forecasting. CoRR Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean P. Foster, Tim Januschowski
2019	A*	`conf`	Forecasting Big Time Series: Theory and Practice. KDD Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang
2019	J	`jnl`	GluonTS: Probabilistic Time Series Models in Python. CoRR Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Sundar Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang
2019	J	`jnl`	High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes. CoRR David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus
2019	A*	`conf`	High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes. NeurIPS David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus
2019	A	`conf`	Probabilistic Forecasting with Spline Quantile Function RNNs. AISTATS Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski
2018	A*	`conf`	Deep State Space Models for Time Series Forecasting. NeurIPS Syama Sundar Rangapuram, Matthias W. Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, Tim Januschowski
2018	J	`jnl`	Forecasting Big Time Series: Old and New. Proc. VLDB Endow. Christos Faloutsos, Jan Gasthaus, Tim Januschowski, Yuyang Wang
2017	J	`jnl`	Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale. CoRR Matthias W. Seeger, Syama Sundar Rangapuram, Yuyang Wang, David Salinas, Jan Gasthaus, Tim Januschowski, Valentin Flunkert
2017	J	`jnl`	DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks. CoRR Valentin Flunkert, David Salinas, Jan Gasthaus
2017	J	`jnl`	GP-Select: Accelerating EM Using Adaptive Subspace Preselection. Neural Comput. Jacquelyn A. Shelton, Jan Gasthaus, Zhenwen Dai, Jörg Lücke, Arthur Gretton
2017	J	`jnl`	Probabilistic Demand Forecasting at Scale. Proc. VLDB Endow. Joos-Hendrik Boese, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Dustin Lange, David Salinas, Sebastian Schelter, Matthias W. Seeger, Bernie Wang
2014	J	`jnl`	GP-select: Accelerating EM using adaptive subspace preselection. CoRR Jacquelyn A. Shelton, Jan Gasthaus, Zhenwen Dai, Jörg Lücke, Arthur Gretton
2011	J	`jnl`	The sequence memoizer. Commun. ACM Frank D. Wood, Jan Gasthaus, Cédric Archambeau, Lancelot James, Yee Whye Teh
2010	—	`conf`	Improvements to the Sequence Memoizer. NIPS Jan Gasthaus, Yee Whye Teh
2010	B	`conf`	Lossless Compression Based on the Sequence Memoizer. DCC Jan Gasthaus, Frank D. Wood, Yee Whye Teh
2009	A*	`conf`	A stochastic memoizer for sequence data. ICML Frank D. Wood, Cédric Archambeau, Jan Gasthaus, Lancelot James, Yee Whye Teh
2008	—	`conf`	Dependent Dirichlet Process Spike Sorting. NIPS Jan Gasthaus, Frank D. Wood, Dilan Görür, Yee Whye Teh