Oleksandr Shchur

32 papers A* 6A 1Journal 20Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Chronos-2: From Univariate to Universal Forecasting. CoRR Abdul Fatir Ansari, Oleksandr Shchur, Jaris Küken, Andreas Auer, Boran Han, Pedro Mercado, Syama Sundar Rangapuram, Huibin Shen, Lorenzo Stella, Xiyuan Zhang, Mononito Goswami, Shubham Kapoor, Danielle C. Maddix, Pablo Guerron, Tony Hu, Junming Yin, Nick Erickson, Prateek Mutalik Desai, Hao Wang, Huzefa Rangwala, George Karypis, Yuyang Wang, Michael Bohlke-Schneider
2025	A	`conf`	ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables. AISTATS 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, Syama Sundar Rangapuram
2025	J	`jnl`	ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables. CoRR 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, Syama Sundar Rangapuram
2025	—	`conf`	Multi-layer Stack Ensembles for Time Series Forecasting. AutoML Nathanael Bosch, Oleksandr Shchur, Nick Erickson, Michael Bohlke-Schneider, Ali Caner Türkmen
2025	J	`jnl`	Multi-layer Stack Ensembles for Time Series Forecasting. CoRR Nathanael Bosch, Oleksandr Shchur, Nick Erickson, Michael Bohlke-Schneider, Caner Türkmen
2025	J	`jnl`	Test-Time Efficient Pretrained Model Portfolios for Time Series Forecasting. CoRR Mert Kayaalp, Caner Turkmen, Oleksandr Shchur, Pedro Mercado, Abdul Fatir Ansari, Michael Bohlke-Schneider, Bernie Wang
2025	J	`jnl`	Understanding Transformers for Time Series: Rank Structure, Flow-of-ranks, and Compressibility. CoRR Annan Yu, Danielle C. Maddix, Boran Han, Xiyuan Zhang, Abdul Fatir Ansari, Oleksandr Shchur, Christos Faloutsos, Andrew Gordon Wilson, Michael W. Mahoney, Yuyang Wang
2025	J	`jnl`	Understanding the Implicit Biases of Design Choices for Time Series Foundation Models. CoRR Annan Yu, Danielle C. Maddix, Boran Han, Xiyuan Zhang, Abdul Fatir Ansari, Oleksandr Shchur, Christos Faloutsos, Andrew Gordon Wilson, Michael W. Mahoney, Yuyang Wang
2025	J	`jnl`	fev-bench: A Realistic Benchmark for Time Series Forecasting. CoRR Oleksandr Shchur, Abdul Fatir Ansari, Caner Turkmen, Lorenzo Stella, Nick Erickson, Pablo Guerron, Michael Bohlke-Schneider, Yuyang Wang
2024	J	`jnl`	Chronos: Learning the Language of Time Series. CoRR 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
2024	J	`jnl`	Chronos: Learning the Language of Time Series. Trans. Mach. Learn. Res. 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, Hao Wang, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Bernie Wang
2024	—	`conf`	Forecasting Algorithms for Intelligent Resource Scaling: An Experimental Analysis. SoCC Yanlei Diao, Dominik Horn, Andreas Kipf, Oleksandr Shchur, Ines Benito, Wenjian Dong, Davide Pagano, Pascal Pfeil, Vikram Nathan, Balakrishnan Narayanaswamy, Tim Kraska
2023	A*	`conf`	Add and Thin: Diffusion for Temporal Point Processes. NeurIPS David Lüdke, Marin Bilos, Oleksandr Shchur, Marten Lienen, Stephan Günnemann
2023	J	`jnl`	Add and Thin: Diffusion for Temporal Point Processes. CoRR David Lüdke, Marin Bilos, Oleksandr Shchur, Marten Lienen, Stephan Günnemann
2023	—	`conf`	AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. AutoML Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Bernie Wang
2023	J	`jnl`	AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. CoRR Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Yuyang Wang
2022	—	`—`	Modeling Continuous-time Event Data with Neural Temporal Point Processes. Oleksandr Shchur
2021	A*	`conf`	Detecting Anomalous Event Sequences with Temporal Point Processes. NeurIPS Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann
2021	J	`jnl`	Detecting Anomalous Event Sequences with Temporal Point Processes. CoRR Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann
2021	A*	`conf`	Neural Temporal Point Processes: A Review. IJCAI Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann
2021	J	`jnl`	Neural Temporal Point Processes: A Review. CoRR Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann
2020	A*	`conf`	Fast and Flexible Temporal Point Processes with Triangular Maps. NeurIPS Oleksandr Shchur, Nicholas Gao, Marin Bilos, Stephan Günnemann
2020	J	`jnl`	Fast and Flexible Temporal Point Processes with Triangular Maps. CoRR Oleksandr Shchur, Nicholas Gao, Marin Bilos, Stephan Günnemann
2020	A*	`conf`	Intensity-Free Learning of Temporal Point Processes. ICLR Oleksandr Shchur, Marin Bilos, Stephan Günnemann
2019	J	`jnl`	Intensity-Free Learning of Temporal Point Processes. CoRR Oleksandr Shchur, Marin Bilos, Stephan Günnemann
2019	J	`jnl`	Overlapping Community Detection with Graph Neural Networks. CoRR Oleksandr Shchur, Stephan Günnemann
2018	—	`conf`	Anomaly Detection in Car-Booking Graphs. ICDM Workshops Oleksandr Shchur, Aleksandar Bojchevski, Mohamed Farghal, Stephan Günnemann, Yusuf Saber
2018	J	`jnl`	Dual-Primal Graph Convolutional Networks. CoRR Federico Monti, Oleksandr Shchur, Aleksandar Bojchevski, Or Litany, Stephan Günnemann, Michael M. Bronstein
2018	A*	`conf`	NetGAN: Generating Graphs via Random Walks. ICML Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann
2018	J	`jnl`	NetGAN: Generating Graphs via Random Walks. CoRR Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann
2018	J	`jnl`	Pitfalls of Graph Neural Network Evaluation. CoRR Oleksandr Shchur, Maximilian Mumme, Aleksandar Bojchevski, Stephan Günnemann
2017	J	`jnl`	Introduction to Tensor Decompositions and their Applications in Machine Learning. CoRR Stephan Rabanser, Oleksandr Shchur, Stephan Günnemann