Introduction to Tensor Decompositions and their Applications in Machine Learning. - Stephan Rabanser; Oleksandr Shchur; Stephan Günnemann (CoRR, 2017)

Anomaly Detection in Car-Booking Graphs. - Oleksandr Shchur; Aleksandar Bojchevski; Mohamed Farghal; Stephan Günnemann; Yusuf Saber (ICDM Workshops, 2018)

NetGAN: Generating Graphs via Random Walks. - Aleksandar Bojchevski; Oleksandr Shchur; Daniel Zügner; Stephan Günnemann (ICML, 2018)

Dual-Primal Graph Convolutional Networks. - Federico Monti; Oleksandr Shchur; Aleksandar Bojchevski; Or Litany; Stephan Günnemann; Michael M. Bronstein (CoRR, 2018)

Pitfalls of Graph Neural Network Evaluation. - Oleksandr Shchur; Maximilian Mumme; Aleksandar Bojchevski; Stephan Günnemann (CoRR, 2018)

Overlapping Community Detection with Graph Neural Networks. - Oleksandr Shchur; Stephan Günnemann (CoRR, 2019)

Intensity-Free Learning of Temporal Point Processes. - Oleksandr Shchur; Marin Bilos; Stephan Günnemann (ICLR, 2020)

Fast and Flexible Temporal Point Processes with Triangular Maps. - Oleksandr Shchur; Nicholas Gao; Marin Bilos; Stephan Günnemann (NeurIPS, 2020)

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

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

Modeling Continuous-time Event Data with Neural Temporal Point Processes. - Oleksandr Shchur (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)

Add and Thin: Diffusion for Temporal Point Processes. - David Lüdke; Marin Bilos; Oleksandr Shchur; Marten Lienen; Stephan Günnemann (NeurIPS, 2023)

Forecasting Algorithms for Intelligent Resource Scaling: An Experimental Analysis. - Yanlei Diao; Dominik Horn; Andreas Kipf; Oleksandr Shchur; Ines Benito; Wenjian Dong; Davide Pagano; Pascal Pfeil; Vikram Nathan; Balakrishnan Narayanaswamy; Tim Kraska (SoCC, 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. (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)

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)