Tim Januschowski

Citirano

	Sve	Od 2020.
Citati	7830	7488
H-indeks	29	27
i10-indeks	48	44

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Suautori

Jan GasthausAWS AI Labs, Amazon Web ServicesPotvrđena adresa e-pošte na ucl.ac.uk
Valentin FlunkertAmazonPotvrđena adresa e-pošte na amazon.com
Yuyang (Bernie) WangPrincipal Scientist, AWS AIPotvrđena adresa e-pošte na mit.edu
David SalinasUniversity of FreiburgPotvrđena adresa e-pošte na ens-lyon.org
Syama Sundar RangapuramAmazonPotvrđena adresa e-pošte na amazon.de
Lorenzo StellaAmazon, AWSPotvrđena adresa e-pošte na amazon.com
Michael Bohlke-SchneiderMachine Learning Manager at AmazonPotvrđena adresa e-pošte na amazon.com
Caner TürkmenAmazon ResearchPotvrđena adresa e-pošte na amazon.com
Konstantinos BenidisAmazonPotvrđena adresa e-pošte na amazon.com
Danielle MaddixAWS AI | Stanford UniversityPotvrđena adresa e-pošte na stanford.edu
Laurent CallotPrincipal scientist, AWS AI LabsPotvrđena adresa e-pošte na amazon.com
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinPotvrđena adresa e-pošte na amazon.de
Sebastian SchelterProfessor at BIFOLD & TU BerlinPotvrđena adresa e-pošte na tu-berlin.de
Alexander AlexandrovResearch Assistant, TU BerlinPotvrđena adresa e-pošte na tu-berlin.de
Alex SmolaBoson AIPotvrđena adresa e-pošte na smola.org
Richard KurleTechnical University MunichPotvrđena adresa e-pošte na tum.de
Stephan GünnemannProfessor of Computer Science, Technical University of MunichPotvrđena adresa e-pošte na in.tum.de
Christos FaloutsosCMUPotvrđena adresa e-pošte na cs.cmu.edu
François-Xavier AubetGoogle DeepMindPotvrđena adresa e-pošte na deepmind.com
Hilaf HassonPrincipal Research Scientist at IntuitPotvrđena adresa e-pošte na intuit.com

Prati

Tim Januschowski

Databricks (prior: Zalando, AWS/Amazon, TU Berlin, University College Cork, Zuse Institute Berlin)

Potvrđena adresa e-pošte na databricks.com

Forecasting Mathematical Programming Machine Learning


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
DeepAR: Probabilistic forecasting with autoregressive recurrent networks D Salinas, V Flunkert, J Gasthaus, T Januschowski International journal of forecasting 36 (3), 1181-1191, 2020	2522	2020
Forecasting: theory and practice F Petropoulos, D Apiletti, V Assimakopoulos, MZ Babai, DK Barrow, ... International Journal of forecasting 38 (3), 705-871, 2022	915	2022
Deep state space models for time series forecasting SS Rangapuram, MW Seeger, J Gasthaus, L Stella, Y Wang, ... Advances in neural information processing systems 31, 2018	897	2018
Gluonts: Probabilistic and neural time series modeling in python A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ... Journal of Machine Learning Research 21 (116), 1-6, 2020	400*	2020
Deep learning for time series forecasting: Tutorial and literature survey K Benidis, SS Rangapuram, V Flunkert, Y Wang, D Maddix, C Turkmen, ... ACM Computing Surveys 55 (6), 1-36, 2022	361*	2022
Criteria for classifying forecasting methods T Januschowski, J Gasthaus, Y Wang, D Salinas, V Flunkert, ... International Journal of Forecasting 36 (1), 167-177, 2020	252	2020
Deep factors for forecasting Y Wang, A Smola, D Maddix, J Gasthaus, D Foster, T Januschowski International conference on machine learning, 6607-6617, 2019	235	2019
On challenges in machine learning model management S Schelter, F Biessmann, T Januschowski, D Salinas, S Seufert, ...	233	2015
Probabilistic forecasting with spline quantile function RNNs J Gasthaus, K Benidis, Y Wang, SS Rangapuram, D Salinas, V Flunkert, ... The 22nd international conference on artificial intelligence and statistics …, 2019	202	2019
Probabilistic demand forecasting at scale JH Böse, V Flunkert, J Gasthaus, T Januschowski, D Lange, D Salinas, ... Proceedings of the VLDB Endowment 10 (12), 1694-1705, 2017	181	2017
Elastic machine learning algorithms in amazon sagemaker E Liberty, Z Karnin, B Xiang, L Rouesnel, B Coskun, R Nallapati, ... Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020	145	2020
Normalizing kalman filters for multivariate time series analysis E de Bézenac, SS Rangapuram, K Benidis, M Bohlke-Schneider, R Kurle, ... Advances in Neural Information Processing Systems 33, 2995-3007, 2020	140	2020
Neural temporal point processes: A review O Shchur, AC Türkmen, T Januschowski, S Günnemann arXiv preprint arXiv:2104.03528, 2021	116	2021
Forecasting with trees T Januschowski, Y Wang, K Torkkola, T Erkkilä, H Hasson, J Gasthaus International Journal of Forecasting 38 (4), 1473-1481, 2022	111	2022
End-to-end learning of coherent probabilistic forecasts for hierarchical time series SS Rangapuram, LD Werner, K Benidis, P Mercado, J Gasthaus, ... International Conference on Machine Learning, 8832-8843, 2021	88	2021
Forecasting big time series: old and new C Faloutsos, J Gasthaus, T Januschowski, Y Wang Proceedings of the VLDB Endowment 11 (12), 2102-2105, 2018	88	2018
Neural flows: Efficient alternative to neural ODEs M Biloš, J Sommer, SS Rangapuram, T Januschowski, S Günnemann Advances in neural information processing systems 34, 21325-21337, 2021	84	2021
RTP: robust tenant placement for elastic in-memory database clusters J Schaffner, T Januschowski, M Kercher, T Kraska, H Plattner, MJ Franklin, ... Proceedings of the 2013 ACM SIGMOD International Conference on Management of …, 2013	60	2013
Psa-gan: Progressive self attention gans for synthetic time series J Paul, BS Michael, M Pedro, K Shubham, SN Rajbir, F Valentin, G Jan, ... arXiv preprint arXiv:2108.00981, 2021	58*	2021
Forecasting intermittent and sparse time series: A unified probabilistic framework via deep renewal processes AC Türkmen, T Januschowski, Y Wang, AT Cemgil Plos one 16 (11), e0259764, 2021	51*	2021

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