Political interest and tendency prediction from microblog data. - Ali Caner Türkmen; Ali Taylan Cemgil (SIU, 2014)

An application of deep learning for trade signal prediction in financial markets. - Ali Caner Türkmen; Ali Taylan Cemgil (SIU, 2015)

A Review of Nonnegative Matrix Factorization Methods for Clustering. - Ali Caner Türkmen (CoRR, 2015)

Sentiment extraction from financial public disclosure documents. - Ali Caner Türkmen (MIDAS@PKDD/ECML, 2016)

Text classification with coupled matrix factorization. - Ali Caner Türkmen; Ali Taylan Cemgil (SIU, 2016)

Testing for Self-excitation in Financial Events: A Bayesian Approach. - Ali Caner Türkmen; Ali Taylan Cemgil (MIDAS/PAP@PKDD/ECML, 2018)

FastPoint: Scalable Deep Point Processes. - Ali Caner Türkmen; Yuyang Wang 001; Alexander J. Smola (ECML/PKDD (2), 2019)

GluonTS: Probabilistic Time Series Models in Python. - Alexander Alexandrov 001; 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; et al. (CoRR, 2019)

A Bayesian Choice Model for Eliminating Feedback Loops. - Gökhan Çapan; Ilker Gündogdu; Ali Caner Türkmen; Cagri Sofuoglu; Ali Taylan Cemgil (CoRR, 2019)

Intermittent Demand Forecasting with Deep Renewal Processes. - Ali Caner Türkmen; Yuyang Wang 001; Tim Januschowski (CoRR, 2019)

Neural forecasting: Introduction and literature overview. - Konstantinos Benidis; Syama Sundar Rangapuram; Valentin Flunkert; Bernie Wang 001; Danielle C. Maddix; Ali Caner Türkmen; Jan Gasthaus; Michael Bohlke-Schneider; David Salinas; Lorenzo Stella; Laurent Callot; Tim Januschowski (CoRR, 2020)

Intermittent Demand Forecasting with Renewal Processes. - Ali Caner Türkmen; Tim Januschowski; Yuyang Wang 001; Ali Taylan Cemgil (CoRR, 2020)

GluonTS: Probabilistic and Neural Time Series Modeling in Python. - Alexander Alexandrov 001; 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; et al. (J. Mach. Learn. Res., 2020)

Clustering Event Streams With Low Rank Hawkes Processes. - Ali Caner Türkmen; Gökhan Çapan; Ali Taylan Cemgil (IEEE Signal Process. Lett., 2020)

Fast high-dimensional temporal point processes with applications (Hızlı yüksek boyutlu zamansal nokta süreçleri ve uygulamaları) - Ali Caner Türkmen (2020)

Neural Temporal Point Processes: A Review. - Oleksandr Shchur; Ali Caner Türkmen; Tim Januschowski; Stephan Günnemann (IJCAI, 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 001; Tim Januschowski (NeurIPS, 2021)

Detecting Anomalous Event Sequences with Temporal Point Processes. - Oleksandr Shchur; Ali Caner Türkmen; Tim Januschowski; Jan Gasthaus; Stephan Günnemann (NeurIPS, 2021)

Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies. - Lenon Minorics; Ali Caner Türkmen; David Kernert; Patrick Blöbaum; Laurent Callot; Dominik Janzing (AISTATS, 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)

AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. - Oleksandr Shchur; Ali Caner Türkmen; Nick Erickson; Huibin Shen; Alexander Shirkov; Tony Hu; Bernie Wang 001 (AutoML, 2023)

Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. - Konstantinos Benidis; Syama Sundar Rangapuram; Valentin Flunkert; Yuyang Wang 001; Danielle C. Maddix; Ali Caner Türkmen; Jan Gasthaus; Michael Bohlke-Schneider; David Salinas; Lorenzo Stella; François-Xavier Aubet; Laurent Callot; et al. (ACM Comput. Surv., 2023)

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; et al. (CoRR, 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; et al. (Trans. Mach. Learn. Res., 2024)

A Flexible Forecasting Stack. - Tim Januschowski; Yuyang Wang 001; Jan Gasthaus; Syama Sundar Rangapuram; Caner Türkmen; Jasper Zschiegner; Lorenzo Stella; Michael Bohlke-Schneider; Danielle C. Maddix; Konstantinos Benidis; Alexander Alexandrov 001; Christos Faloutsos; et al. (Proc. VLDB Endow., 2024)

ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables. - Sebastian Pineda Arango; Pedro Mercado; Shubham Kapoor; Abdul Fatir Ansari; Lorenzo Stella; Huibin Shen; Hugo Senetaire; Ali Caner Türkmen; Oleksandr Shchur; Danielle C. Maddix; Michael Bohlke-Schneider; Bernie Wang 001; et al. (AISTATS, 2025)

ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables. - Sebastian Pineda-Arango; Pedro Mercado; Shubham Kapoor; Abdul Fatir Ansari; Lorenzo Stella; Huibin Shen; Hugo Senetaire; Caner Turkmen; Oleksandr Shchur; Danielle C. Maddix; Michael Bohlke-Schneider; Yuyang Wang 001; et al. (CoRR, 2025)

MLZero: A Multi-Agent System for End-to-end Machine Learning Automation. - Haoyang Fang; Boran Han; Nick Erickson; Xiyuan Zhang; Su Zhou; Anirudh Dagar; Jiani Zhang 003; Ali Caner Türkmen; Cuixiong Hu; Huzefa Rangwala; Ying Nian Wu; Yuyang Wang 001; et al. (CoRR, 2025)