Ali Caner Türkmen

According to our database, Ali Caner Türkmen authored at least 23 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Chronos: Learning the Language of Time Series.

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

CoRR, 2024

2023

Deep Learning for Time Series Forecasting: Tutorial and Literature Survey.

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

ACM Comput. Surv., 2023

AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting.

Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Bernie Wang

Proceedings of the International Conference on Automated Machine Learning, 2023

2022

Dirichlet-Luce choice model for learning from interactions.

Gökhan Çapan, Ilker Gündogdu, Ali Caner Türkmen, Ali Taylan Cemgil

User Model. User Adapt. Interact., 2022

Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies.

Lenon Minorics, Ali Caner Türkmen, David Kernert, Patrick Blöbaum, Laurent Callot, Dominik Janzing

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Detecting Anomalous Event Sequences with Temporal Point Processes.

Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Explicit Duration Switching Models for Time Series.

Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Bernie Wang, Tim Januschowski

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural Temporal Point Processes: A Review.

Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020

Fast high-dimensional temporal point processes with applications (Hızlı yüksek boyutlu zamansal nokta süreçleri ve uygulamaları)

Ali Caner Türkmen

PhD thesis, 2020

Clustering Event Streams With Low Rank Hawkes Processes.

Ali Caner Türkmen, Gökhan Çapan, Ali Taylan Cemgil

IEEE Signal Process. Lett., 2020

GluonTS: Probabilistic and Neural Time Series Modeling in Python.

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

J. Mach. Learn. Res., 2020

Intermittent Demand Forecasting with Renewal Processes.

Ali Caner Türkmen, Tim Januschowski, Yuyang Wang, Ali Taylan Cemgil

CoRR, 2020

Neural forecasting: Introduction and literature overview.

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

CoRR, 2020

2019

Intermittent Demand Forecasting with Deep Renewal Processes.

Ali Caner Türkmen, Yuyang Wang, Tim Januschowski

CoRR, 2019

A Bayesian Choice Model for Eliminating Feedback Loops.

Gökhan Çapan, Ilker Gündogdu, Ali Caner Türkmen, Cagri Sofuoglu, Ali Taylan Cemgil

CoRR, 2019

GluonTS: Probabilistic Time Series Models in Python.

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

CoRR, 2019

FastPoint: Scalable Deep Point Processes.

Ali Caner Türkmen, Yuyang Wang, Alexander J. Smola

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

2018

Testing for Self-excitation in Financial Events: A Bayesian Approach.

Ali Caner Türkmen, Ali Taylan Cemgil

Proceedings of the ECML PKDD 2018 Workshops, 2018

2016

Text classification with coupled matrix factorization.

Ali Caner Türkmen, Ali Taylan Cemgil

Proceedings of the 24th Signal Processing and Communication Application Conference, 2016

Sentiment extraction from financial public disclosure documents.

Ali Caner Türkmen

Proceedings of the First Workshop on MIning DAta for financial applicationS (MIDAS 2016) co-located with the 2016 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2016), 2016

2015

A Review of Nonnegative Matrix Factorization Methods for Clustering.

Ali Caner Türkmen

CoRR, 2015

An application of deep learning for trade signal prediction in financial markets.

Ali Caner Türkmen, Ali Taylan Cemgil

Proceedings of the 2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015

2014

Political interest and tendency prediction from microblog data.

Ali Caner Türkmen, Ali Taylan Cemgil

Proceedings of the 2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014