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Tim Januschowski
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2020 – today
- 2024
- [j7]Tim Januschowski, Yuyang Wang, Jan Gasthaus, Syama Sundar Rangapuram, Caner Turkmen, Jasper Zschiegner, Lorenzo Stella, Michael Bohlke-Schneider, Danielle C. Maddix, Konstantinos Benidis, Alexander Alexandrov, Christos Faloutsos, Sebastian Schelter:
A Flexible Forecasting Stack. Proc. VLDB Endow. 17(12): 3883-3892 (2024) - 2023
- [j6]Konstantinos Benidis
, Syama Sundar Rangapuram
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. ACM Comput. Surv. 55(6): 121:1-121:36 (2023) - [c26]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: 9362-9376 - [i30]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 abs/2305.14406 (2023) - [i29]Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski:
Deep Non-Parametric Time Series Forecaster. CoRR abs/2312.14657 (2023) - [i28]Douglas Schultz, Johannes Stephan, Julian Sieber, Trudie Yeh, Manuel Kunz, Patrick Doupe, Tim Januschowski:
Causal Forecasting for Pricing. CoRR abs/2312.15282 (2023) - 2022
- [c25]Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus:
Multivariate Quantile Function Forecaster. AISTATS 2022: 10603-10621 - [c24]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 - [c23]Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus:
On the detrimental effect of invariances in the likelihood for variational inference. NeurIPS 2022 - [i27]Oliver Borchert, David Salinas, Valentin Flunkert, Tim Januschowski, Stephan Günnemann:
Multi-Objective Model Selection for Time Series Forecasting. CoRR abs/2202.08485 (2022) - [i26]Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus:
Multivariate Quantile Function Forecaster. CoRR abs/2202.11316 (2022) - [i25]Victor Garcia Satorras, Syama Sundar Rangapuram, Tim Januschowski:
Multivariate Time Series Forecasting with Latent Graph Inference. CoRR abs/2203.03423 (2022) - [i24]Michael Bohlke-Schneider, Shubham Kapoor, Tim Januschowski:
Resilient Neural Forecasting Systems. CoRR abs/2203.08492 (2022) - [i23]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 abs/2203.11103 (2022) - [i22]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 abs/2206.14342 (2022) - [i21]Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus:
On the detrimental effect of invariances in the likelihood for variational inference. CoRR abs/2209.07157 (2022) - [i20]Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider, Laurent Callot:
Criteria for Classifying Forecasting Methods. CoRR abs/2212.03523 (2022) - 2021
- [c22]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: 8832-8843 - [c21]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann:
Neural Temporal Point Processes: A Review. IJCAI 2021: 4585-4593 - [c20]Hilaf Hasson, Bernie Wang, Tim Januschowski, Jan Gasthaus:
Probabilistic Forecasting: A Level-Set Approach. NeurIPS 2021: 6404-6416 - [c19]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann:
Detecting Anomalous Event Sequences with Temporal Point Processes. NeurIPS 2021: 13419-13431 - [c18]Marin Bilos, Johanna Sommer, Syama Sundar Rangapuram, Tim Januschowski, Stephan Günnemann:
Neural Flows: Efficient Alternative to Neural ODEs. NeurIPS 2021: 21325-21337 - [c17]Quentin Rebjock, Baris Kurt, Tim Januschowski, Laurent Callot:
Online false discovery rate control for anomaly detection in time series. NeurIPS 2021: 26487-26498 - [c16]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: 29949-29961 - [i19]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann:
Neural Temporal Point Processes: A Review. CoRR abs/2104.03528 (2021) - [i18]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann:
Detecting Anomalous Event Sequences with Temporal Point Processes. CoRR abs/2106.04465 (2021) - [i17]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 abs/2108.00981 (2021) - [i16]Daniel Zügner, François-Xavier Aubet, Victor Garcia Satorras, Tim Januschowski, Stephan Günnemann, Jan Gasthaus:
A Study of Joint Graph Inference and Forecasting. CoRR abs/2109.04979 (2021) - [i15]Marin Bilos, Johanna Sommer, Syama Sundar Rangapuram, Tim Januschowski, Stephan Günnemann:
Neural Flows: Efficient Alternative to Neural ODEs. CoRR abs/2110.13040 (2021) - [i14]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 abs/2110.13878 (2021) - [i13]Riccardo Grazzi, Valentin Flunkert, David Salinas, Tim Januschowski, Matthias W. Seeger, Cédric Archambeau:
Meta-Forecasting by combining Global Deep Representations with Local Adaptation. CoRR abs/2111.03418 (2021) - [i12]Quentin Rebjock, Baris Kurt, Tim Januschowski, Laurent Callot:
Online false discovery rate control for anomaly detection in time series. CoRR abs/2112.03196 (2021) - 2020
- [j5]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: 116:1-116:6 (2020) - [c15]Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus:
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models. ICSOC Workshops 2020: 97-109 - [c14]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 - [c13]Michael Bohlke-Schneider, Shubham Kapoor, Tim Januschowski:
Resilient Neural Forecasting Systems. DEEM@SIGMOD 2020: 4:1-4:5 - [c12]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: 731-737 - [c11]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 - [c10]Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang:
Forecasting Big Time Series: Theory and Practice. WWW (Companion Volume) 2020: 320-321 - [i11]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 abs/2004.10240 (2020) - [i10]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 abs/2005.10111 (2020) - [i9]Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus:
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models. CoRR abs/2007.15541 (2020) - [i8]Valentin Flunkert, Quentin Rebjock, Joel Castellon, Laurent Callot, Tim Januschowski:
A simple and effective predictive resource scaling heuristic for large-scale cloud applications. CoRR abs/2008.01215 (2020) - [i7]Ali Caner Türkmen, Tim Januschowski, Yuyang Wang, Ali Taylan Cemgil:
Intermittent Demand Forecasting with Renewal Processes. CoRR abs/2010.01550 (2020) - [i6]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
Forecasting: theory and practice. CoRR abs/2012.03854 (2020)
2010 – 2019
- 2019
- [c9]Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski:
Probabilistic Forecasting with Spline Quantile Function RNNs. AISTATS 2019: 1901-1910 - [c8]Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean P. Foster, Tim Januschowski:
Deep Factors for Forecasting. ICML 2019: 6607-6617 - [c7]Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang:
Forecasting Big Time Series: Theory and Practice. KDD 2019: 3209-3210 - [c6]Christos Faloutsos, Jan Gasthaus, Tim Januschowski, Yuyang Wang:
Classical and Contemporary Approaches to Big Time Series Forecasting. SIGMOD Conference 2019: 2042-2047 - [c5]Vincent Deuschle, Alexander Alexandrov, Tim Januschowski, Volker Markl:
End-to-End Benchmarking of Deep Learning Platforms. TPCTC 2019: 116-132 - [i5]Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean P. Foster, Tim Januschowski:
Deep Factors for Forecasting. CoRR abs/1905.12417 (2019) - [i4]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 abs/1906.05264 (2019) - [i3]Ali Caner Türkmen, Yuyang Wang, Tim Januschowski:
Intermittent Demand Forecasting with Deep Renewal Processes. CoRR abs/1911.10416 (2019) - 2018
- [j4]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): 5-15 (2018) - [j3]Christos Faloutsos, Jan Gasthaus, Tim Januschowski, Yuyang Wang:
Forecasting Big Time Series: Old and New. Proc. VLDB Endow. 11(12): 2102-2105 (2018) - [c4]Syama Sundar Rangapuram, Matthias W. Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, Tim Januschowski:
Deep State Space Models for Time Series Forecasting. NeurIPS 2018: 7796-7805 - 2017
- [j2]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): 1694-1705 (2017) - [i2]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 abs/1709.07638 (2017) - 2013
- [c3]Jan Schaffner, Tim Januschowski:
Realistic tenant traces for enterprise DBaaS. ICDE Workshops 2013: 29-35 - [c2]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: 773-784 - 2011
- [j1]Tim Januschowski, Marc E. Pfetsch
The maximum k-colorable subgraph problem and orbitopes. Discret. Optim. 8(3): 478-494 (2011) - [c1]Tim Januschowski, Marc E. Pfetsch
Branch-Cut-and-Propagate for the Maximum k-Colorable Subgraph Problem with Symmetry. CPAIOR 2011: 99-116 - 2010
- [i1]Tim Januschowski, Barbara M. Smith, Marc R. C. van Dongen:
Symmetry Breaking with Polynomial Delay. CoRR abs/1012.5585 (2010)
Coauthor Index
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