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ORCIDAli Caner Türkmen
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- affiliation: Boğaziçi University, Istanbul, Turkey
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2020 – today
- 2024
[i11]Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Türkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda-Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang:
Chronos: Learning the Language of Time Series. CoRR abs/2403.07815 (2024)- 2023
- [j4]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): 121:1-121:36 (2023) - [c11]Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Bernie Wang:
AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. AutoML 2023: 9/1-21 - [i10]Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Yuyang Wang:
AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. CoRR abs/2308.05566 (2023) - 2022
- [j3]Gökhan Çapan, Ilker Gündogdu, Ali Caner Türkmen, Ali Taylan Cemgil:
Dirichlet-Luce choice model for learning from interactions. User Model. User Adapt. Interact. 32(4): 611-648 (2022) - [c10]Lenon Minorics, Ali Caner Türkmen, David Kernert, Patrick Blöbaum, Laurent Callot, Dominik Janzing:
Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies. AISTATS 2022: 10534-10554 - 2021
- [c9]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann:
Neural Temporal Point Processes: A Review. IJCAI 2021: 4585-4593 - [c8]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann:
Detecting Anomalous Event Sequences with Temporal Point Processes. NeurIPS 2021: 13419-13431 - [c7]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 - [i9]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann:
Neural Temporal Point Processes: A Review. CoRR abs/2104.03528 (2021) - [i8]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann:
Detecting Anomalous Event Sequences with Temporal Point Processes. CoRR abs/2106.04465 (2021) - [i7]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) - 2020
- [b1]Ali Caner Türkmen:
Fast high-dimensional temporal point processes with applications (Hızlı yüksek boyutlu zamansal nokta süreçleri ve uygulamaları). Boğaziçi University, Turkey, 2020 - [j2]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) - [j1]Ali Caner Türkmen, Gökhan Çapan, Ali Taylan Cemgil:
Clustering Event Streams With Low Rank Hawkes Processes. IEEE Signal Process. Lett. 27: 1575-1579 (2020) - [i6]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) - [i5]Ali Caner Türkmen, Tim Januschowski, Yuyang Wang, Ali Taylan Cemgil:
Intermittent Demand Forecasting with Renewal Processes. CoRR abs/2010.01550 (2020)
2010 – 2019
- 2019
- [c6]Ali Caner Türkmen, Yuyang Wang, Alexander J. Smola:
FastPoint: Scalable Deep Point Processes. ECML/PKDD (2) 2019: 465-480 - [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]Gökhan Çapan, Ilker Gündogdu, Ali Caner Türkmen, Cagri Sofuoglu, Ali Taylan Cemgil:
A Bayesian Choice Model for Eliminating Feedback Loops. CoRR abs/1908.05640 (2019) - [i2]Ali Caner Türkmen, Yuyang Wang, Tim Januschowski:
Intermittent Demand Forecasting with Deep Renewal Processes. CoRR abs/1911.10416 (2019) - 2018
- [c5]Ali Caner Türkmen, Ali Taylan Cemgil:
Testing for Self-excitation in Financial Events: A Bayesian Approach. MIDAS/PAP@PKDD/ECML 2018: 95-102 - 2016
- [c4]Ali Caner Türkmen:
Sentiment extraction from financial public disclosure documents. MIDAS@PKDD/ECML 2016: 67-72 - [c3]Ali Caner Türkmen, Ali Taylan Cemgil:
Text classification with coupled matrix factorization. SIU 2016: 1697-1700 - 2015
- [c2]Ali Caner Türkmen, Ali Taylan Cemgil:
An application of deep learning for trade signal prediction in financial markets. SIU 2015: 2521-2524 - [i1]Ali Caner Türkmen:
A Review of Nonnegative Matrix Factorization Methods for Clustering. CoRR abs/1507.03194 (2015) - 2014
- [c1]Ali Caner Türkmen, Ali Taylan Cemgil:
Political interest and tendency prediction from microblog data. SIU 2014: 1327-1330
Coauthor Index
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