Tim Januschowski

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 57

Top Topics

Exponential Smoothing

Demand Forecasting

Point Processes

Multivariate Time Series

Top Venues

Proc. VLDB Endow.

Publications

Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski
Deep Non-Parametric Time Series Forecaster. CoRR (2023)
Manuel Kunz, Stefan Birr, Mones Raslan, Lei Ma, Zhen Li, Adèle Gouttes, Mateusz Koren, Tofigh Naghibi, Johannes Stephan, Mariia Bulycheva, Matthias Grzeschik, Armin Kekic, Michael Narodovitch, Kashif Rasul, Julian Sieber, Tim Januschowski
Deep Learning based Forecasting: a case study from the online fashion industry. CoRR (2023)
Douglas Schultz, Johannes Stephan, Julian Sieber, Trudie Yeh, Manuel Kunz, Patrick Doupe, Tim Januschowski
Causal Forecasting for Pricing. CoRR (2023)
Syama Sundar Rangapuram, Shubham Kapoor, Rajbir-Singh Nirwan, Pedro Mercado, Tim Januschowski, Yuyang Wang, Michael Bohlke-Schneider
Coherent Probabilistic Forecasting of Temporal Hierarchies. AISTATS (2023)
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
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. ACM Comput. Surv. 55 (6) (2023)
Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
On the detrimental effect of invariances in the likelihood for variational inference. CoRR (2022)
Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus
Multivariate Quantile Function Forecaster. CoRR (2022)
Michael Bohlke-Schneider, Shubham Kapoor, Tim Januschowski
Resilient Neural Forecasting Systems. CoRR (2022)
Victor Garcia Satorras, Syama Sundar Rangapuram, Tim Januschowski
Multivariate Time Series Forecasting with Latent Graph Inference. CoRR (2022)
Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider, Laurent Callot
Criteria for Classifying Forecasting Methods. CoRR (2022)
Déborah Sulem, Michele Donini, Muhammad Bilal Zafar, Francois-Xavier Aubet, Jan Gasthaus, Tim Januschowski, Sanjiv Das, Krishnaram Kenthapadi, Cédric Archambeau
Diverse Counterfactual Explanations for Anomaly Detection in Time Series. CoRR (2022)
Oliver Borchert, David Salinas, Valentin Flunkert, Tim Januschowski, Stephan Günnemann
Multi-Objective Model Selection for Time Series Forecasting. CoRR (2022)
Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Shubham Kapoor, Rajbir-Singh Nirwan, Valentin Flunkert, Jan Gasthaus, Tim Januschowski
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series. ICLR (2022)
Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus
Multivariate Quantile Function Forecaster. AISTATS (2022)
Stephan Rabanser, Tim Januschowski, Kashif Rasul, Oliver Borchert, Richard Kurle, Jan Gasthaus, Michael Bohlke-Schneider, Nicolas Papernot, Valentin Flunkert
Intrinsic Anomaly Detection for Multi-Variate Time Series. CoRR (2022)
Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
On the detrimental effect of invariances in the likelihood for variational inference. NeurIPS (2022)
Quentin Rebjock, Baris Kurt, Tim Januschowski, Laurent Callot
Online false discovery rate control for anomaly detection in time series. NeurIPS (2021)
Hilaf Hasson, Bernie Wang, Tim Januschowski, Jan Gasthaus
Probabilistic Forecasting: A Level-Set Approach. NeurIPS (2021)
Marin Bilos, Johanna Sommer, Syama Sundar Rangapuram, Tim Januschowski, Stephan Günnemann
Neural Flows: Efficient Alternative to Neural ODEs. NeurIPS (2021)
Marin Bilos, Johanna Sommer, Syama Sundar Rangapuram, Tim Januschowski, Stephan Günnemann
Neural Flows: Efficient Alternative to Neural ODEs. CoRR (2021)
Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann
Detecting Anomalous Event Sequences with Temporal Point Processes. CoRR (2021)
Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Rajbir-Singh Nirwan, Shubham Kapoor, Valentin Flunkert, Jan Gasthaus, Tim Januschowski
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series. CoRR (2021)
Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Yuyang Wang, Tim Januschowski
Deep Explicit Duration Switching Models for Time Series. CoRR (2021)
Quentin Rebjock, Baris Kurt, Tim Januschowski, Laurent Callot
Online false discovery rate control for anomaly detection in time series. CoRR (2021)
Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Bernie Wang, Tim Januschowski
Deep Explicit Duration Switching Models for Time Series. NeurIPS (2021)
Riccardo Grazzi, Valentin Flunkert, David Salinas, Tim Januschowski, Matthias W. Seeger, Cédric Archambeau
Meta-Forecasting by combining Global Deep Representations with Local Adaptation. CoRR (2021)
Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann
Neural Temporal Point Processes: A Review. IJCAI (2021)
Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann
Neural Temporal Point Processes: A Review. CoRR (2021)
Daniel Zügner, François-Xavier Aubet, Victor Garcia Satorras, Tim Januschowski, Stephan Günnemann, Jan Gasthaus
A Study of Joint Graph Inference and Forecasting. CoRR (2021)
Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann
Detecting Anomalous Event Sequences with Temporal Point Processes. NeurIPS (2021)
Syama Sundar Rangapuram, Lucien D. Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski
End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series. ICML (2021)
Stephan Rabanser, Tim Januschowski, Valentin Flunkert, David Salinas, Jan Gasthaus
The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models. CoRR (2020)
Quentin Rebjock, Valentin Flunkert, Tim Januschowski, Laurent Callot, Joel Castellon
A Simple and Effective Predictive Resource Scaling Heuristic for Large-scale Cloud Applications. AIDB@VLDB (2020)
Emmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle, Lorenzo Stella, Hilaf Hasson, Patrick Gallinari, Tim Januschowski
Normalizing Kalman Filters for Multivariate Time Series Analysis. NeurIPS (2020)
Fotios Petropoulos, Daniele Apiletti, Vassilios Assimakopoulos, Mohamed Zied Babai, Devon K. Barrow, Souhaib Ben Taieb, Christoph Bergmeir, Ricardo J. Bessa, Jakub Bijak, John E. Boylan, Jethro Browell, Claudio Carnevale, Jennifer L. Castle, Pasquale Cirillo, Michael P. Clements, Clara Cordeiro, Fernando Luiz Cyrino Oliveira, Shari De Baets, Alexander Dokumentov, Joanne Ellison, Piotr Fiszeder, Philip Hans Franses, David T. Frazier, Michael Gilliland, Mustafa Sinan Gönül, Paul Goodwin, Luigi Grossi, Yael Grushka-Cockayne, Mariangela Guidolin, Massimo Guidolin, Ulrich Gunter, Xiaojia Guo, Renato Guseo, Nigel Harvey, David F. Hendry, Ross Hollyman, Tim Januschowski, Jooyoung Jeon, Victor Richmond R. Jose, Yanfei Kang, Anne B. Koehler, Stephan Kolassa, Nikolaos Kourentzes, Sonia Leva, Feng Li
Forecasting: theory and practice. CoRR (2020)
Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang
Forecasting Big Time Series: Theory and Practice. WWW (Companion Volume) (2020)
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
GluonTS: Probabilistic and Neural Time Series Modeling in Python. J. Mach. Learn. Res. 21 (2020)
Ali Caner Türkmen, Tim Januschowski, Yuyang Wang, Ali Taylan Cemgil
Intermittent Demand Forecasting with Renewal Processes. CoRR (2020)
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
Neural forecasting: Introduction and literature overview. CoRR (2020)
Michael Bohlke-Schneider, Shubham Kapoor, Tim Januschowski
Resilient Neural Forecasting Systems. DEEM@SIGMOD (2020)
Valentin Flunkert, Quentin Rebjock, Joel Castellon, Laurent Callot, Tim Januschowski
A simple and effective predictive resource scaling heuristic for large-scale cloud applications. CoRR (2020)
Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models. CoRR (2020)
Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models. ICSOC Workshops (2020)
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
Elastic Machine Learning Algorithms in Amazon SageMaker. SIGMOD Conference (2020)
Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean Foster, Tim Januschowski
Deep Factors for Forecasting. ICML (2019)
Christos Faloutsos, Jan Gasthaus, Tim Januschowski, Yuyang Wang
Classical and Contemporary Approaches to Big Time Series Forecasting. SIGMOD Conference (2019)
Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang
Forecasting Big Time Series: Theory and Practice. KDD (2019)
Ali Caner Türkmen, Yuyang Wang, Tim Januschowski
Intermittent Demand Forecasting with Deep Renewal Processes. CoRR (2019)
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
GluonTS: Probabilistic Time Series Models in Python. CoRR (2019)
Vincent Deuschle, Alexander Alexandrov, Tim Januschowski, Volker Markl
End-to-End Benchmarking of Deep Learning Platforms. TPCTC (2019)
Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean Foster, Tim Januschowski
Deep Factors for Forecasting. CoRR (2019)
Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski
Probabilistic Forecasting with Spline Quantile Function RNNs. AISTATS (2019)
Sebastian Schelter, Felix Bießmann, Tim Januschowski, David Salinas, Stephan Seufert, Gyuri Szarvas
On Challenges in Machine Learning Model Management. IEEE Data Eng. Bull. 41 (4) (2018)
Christos Faloutsos, Jan Gasthaus, Tim Januschowski, Yuyang Wang
Forecasting Big Time Series: Old and New. Proc. VLDB Endow. 11 (12) (2018)
Syama Sundar Rangapuram, Matthias W. Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, Tim Januschowski
Deep State Space Models for Time Series Forecasting. NeurIPS (2018)
Matthias W. Seeger, Syama Sundar Rangapuram, Yuyang Wang, David Salinas, Jan Gasthaus, Tim Januschowski, Valentin Flunkert
Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale. CoRR (2017)
Joos-Hendrik Boese, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Dustin Lange, David Salinas, Sebastian Schelter, Matthias W. Seeger, Bernie Wang
Probabilistic Demand Forecasting at Scale. Proc. VLDB Endow. 10 (12) (2017)
Jan Schaffner, Tim Januschowski
Realistic tenant traces for enterprise DBaaS. ICDE Workshops (2013)
Jan Schaffner, Tim Januschowski, Megan Kercher, Tim Kraska, Hasso Plattner, Michael J. Franklin, Dean Jacobs
RTP: robust tenant placement for elastic in-memory database clusters. SIGMOD Conference (2013)
Tim Januschowski, Marc E. Pfetsch
-Colorable Subgraph Problem with Symmetry. CPAIOR (2011)
Tim Januschowski, Marc E. Pfetsch
The maximum k-colorable subgraph problem and orbitopes. Discret. Optim. 8 (3) (2011)
Tim Januschowski, Barbara M. Smith, Marc R. C. van Dongen
Symmetry Breaking with Polynomial Delay CoRR (2010)