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Zitiert von
Jahr
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
380*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
318*2022
Chronos: Learning the language of time series
AF Ansari, L Stella, C Turkmen, X Zhang, P Mercado, H Shen, O Shchur, ...
arXiv preprint arXiv:2403.07815, 2024
1062024
Neural temporal point processes: A review
O Shchur, AC Türkmen, T Januschowski, S Günnemann
International Joint Conference on Artificial Intelligence (IJCAI), 2021
1022021
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
47*2021
A review of nonnegative matrix factorization methods for clustering
AC Türkmen
arXiv preprint arXiv:1507.03194, 2015
402015
AutoGluon–TimeSeries: AutoML for probabilistic time series forecasting
O Shchur, AC Turkmen, N Erickson, H Shen, A Shirkov, T Hu, B Wang
International Conference on Automated Machine Learning, 9/1-21, 2023
292023
Fastpoint: Scalable deep point processes
AC Türkmen, Y Wang, AJ Smola
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020
292020
Deep explicit duration switching models for time series
AF Ansari, K Benidis, R Kurle, AC Turkmen, H Soh, AJ Smola, B Wang, ...
Advances in Neural Information Processing Systems 34, 29949-29961, 2021
282021
Detecting anomalous event sequences with temporal point processes
O Shchur, AC Turkmen, T Januschowski, J Gasthaus, S Günnemann
Advances in Neural Information Processing Systems 34, 13419-13431, 2021
162021
Dirichlet–Luce choice model for learning from interactions
G Çapan, İ Gündoğdu, AC Türkmen, AT Cemgil
User Modeling and User-Adapted Interaction 32 (4), 611-648, 2022
8*2022
Clustering event streams with low rank Hawkes processes
AC Türkmen, G Çapan, AT Cemgil
IEEE Signal Processing Letters 27, 1575-1579, 2020
62020
Testing granger non-causality in panels with cross-sectional dependencies
L Minorics, C Turkmen, D Kernert, P Bloebaum, L Callot, D Janzing
International Conference on Artificial Intelligence and Statistics, 10534-10554, 2022
22022
Text classification with coupled matrix factorization
AC Türkmen, AT Cemgil
2016 24th Signal Processing and Communication Application Conference (SIU …, 2016
12016
A flexible forecasting stack
T Januschowski, Y Wang, J Gasthaus, S Rangapuram, C Türkmen, ...
Proceedings of the VLDB Endowment 17 (12), 3883-3892, 2024
2024
Fast high-dimensional temporal point processes with applications
AC Türkmen
Thesis (Ph. D.)-Bogazici University. Institute for Graduate Studies in …, 2020
2020
Quantifying Causal Contribution in Rare Event Data
AC Turkmen, D Janzing, O Shchur, L Minorics, L Callot
A causal view on dynamical systems, NeurIPS 2022 workshop, 0
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