Ali Caner Türkmen

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 23

Top Topics

Demand Forecasting

Event Sequences

Point Processes

Top Venues

IEEE Signal Process. Lett.

Publications

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 (2024)
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)
Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Yuyang Wang
AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. CoRR (2023)
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) (2023)
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)
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) (2022)
Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann
Detecting Anomalous Event Sequences with Temporal Point Processes. CoRR (2021)
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 (2021)
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)
Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann
Neural Temporal Point Processes: A Review. IJCAI (2021)
Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann
Neural Temporal Point Processes: A Review. CoRR (2021)
Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann
Detecting Anomalous Event Sequences with Temporal Point Processes. NeurIPS (2021)
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 (2020)
Ali Caner Türkmen, Tim Januschowski, Yuyang Wang, Ali Taylan Cemgil
Intermittent Demand Forecasting with Renewal Processes. CoRR (2020)
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 (2020)
Ali Caner Türkmen, Gökhan Çapan, Ali Taylan Cemgil
Clustering Event Streams With Low Rank Hawkes Processes. IEEE Signal Process. Lett. 27 (2020)
Ali Caner Türkmen, Yuyang Wang, Alexander J. Smola
FastPoint: Scalable Deep Point Processes. ECML/PKDD (2) (2019)
Ali Caner Türkmen, Yuyang Wang, Tim Januschowski
Intermittent Demand Forecasting with Deep Renewal Processes. CoRR (2019)
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 (2019)
Gökhan Çapan, Ilker Gündogdu, Ali Caner Türkmen, Cagri Sofuoglu, Ali Taylan Cemgil
A Bayesian Choice Model for Eliminating Feedback Loops. CoRR (2019)
Ali Caner Türkmen, Ali Taylan Cemgil
Testing for Self-excitation in Financial Events: A Bayesian Approach. MIDAS/PAP@PKDD/ECML (2018)
Ali Caner Türkmen, Ali Taylan Cemgil
Text classification with coupled matrix factorization. SIU (2016)
Ali Caner Türkmen
Sentiment extraction from financial public disclosure documents. MIDAS@PKDD/ECML (2016)
Ali Caner Türkmen
A Review of Nonnegative Matrix Factorization Methods for Clustering. CoRR (2015)
Ali Caner Türkmen, Ali Taylan Cemgil
An application of deep learning for trade signal prediction in financial markets. SIU (2015)
Ali Caner Türkmen, Ali Taylan Cemgil
Political interest and tendency prediction from microblog data. SIU (2014)