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Zitiert von
Zitiert von
Jahr
Gluonts: Probabilistic and neural time series modeling in python
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
The Journal of Machine Learning Research 21 (1), 4629-4634, 2020
295*2020
Neural forecasting: Introduction and literature overview
K Benidis, SS Rangapuram, V Flunkert, B Wang, D Maddix, C Turkmen, ...
arXiv preprint arXiv:2004.10240 6, 2020
213*2020
Neural temporal point processes: A review
O Shchur, AC Türkmen, T Januschowski, S Günnemann
arXiv preprint arXiv:2104.03528, 2021
682021
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
37*2021
A review of nonnegative matrix factorization methods for clustering
AC Türkmen
arXiv preprint arXiv:1507.03194, 2015
362015
Fastpoint: Scalable deep point processes
AC Türkmen, Y Wang, AJ Smola
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020
252020
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
212021
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
92021
Clustering event streams with low rank Hawkes processes
AC Türkmen, G Çapan, AT Cemgil
IEEE Signal Processing Letters 27, 1575-1579, 2020
52020
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
4*2022
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
32023
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
12022
Testing for Self-excitation in Financial Events: A Bayesian Approach
AC Türkmen, AT Cemgil
ECML PKDD 2018 Workshops: MIDAS 2018 and PAP 2018, Dublin, Ireland …, 2019
12019
Modeling high-frequency price data with bounded-delay Hawkes processes
AC Türkmen, AT Cemgil
Mathematical and Statistical Methods for Actuarial Sciences and Finance: MAF …, 2018
12018
Text classification with coupled matrix factorization
AC Türkmen, AT Cemgil
2016 24th Signal Processing and Communication Application Conference (SIU …, 2016
12016
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, 2022
2022
FastPoint: Scalable deep point processes
A Smola, C Turkmen, YB Wang
2019
Neural time series models with GluonTS Time Series Workshop ICML 2019
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
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