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Oleksandr Shchur
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2020 – today
- 2024
- [i12]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 abs/2403.07815 (2024) - 2023
- [c8]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: 9/1-21 - [c7]David Lüdke, Marin Bilos, Oleksandr Shchur, Marten Lienen, Stephan Günnemann:
Add and Thin: Diffusion for Temporal Point Processes. NeurIPS 2023 - [i11]Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Yuyang Wang:
AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. CoRR abs/2308.05566 (2023) - [i10]David Lüdke, Marin Bilos, Oleksandr Shchur, Marten Lienen, Stephan Günnemann:
Add and Thin: Diffusion for Temporal Point Processes. CoRR abs/2311.01139 (2023) - 2022
- [b1]Oleksandr Shchur:
Modeling Continuous-time Event Data with Neural Temporal Point Processes. Technical University of Munich, Germany, 2022 - 2021
- [c6]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann:
Neural Temporal Point Processes: A Review. IJCAI 2021: 4585-4593 - [c5]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann:
Detecting Anomalous Event Sequences with Temporal Point Processes. NeurIPS 2021: 13419-13431 - [i9]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann:
Neural Temporal Point Processes: A Review. CoRR abs/2104.03528 (2021) - [i8]Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann:
Detecting Anomalous Event Sequences with Temporal Point Processes. CoRR abs/2106.04465 (2021) - 2020
- [c4]Oleksandr Shchur, Marin Bilos, Stephan Günnemann:
Intensity-Free Learning of Temporal Point Processes. ICLR 2020 - [c3]Oleksandr Shchur, Nicholas Gao, Marin Bilos, Stephan Günnemann:
Fast and Flexible Temporal Point Processes with Triangular Maps. NeurIPS 2020 - [i7]Oleksandr Shchur, Nicholas Gao, Marin Bilos, Stephan Günnemann:
Fast and Flexible Temporal Point Processes with Triangular Maps. CoRR abs/2006.12631 (2020)
2010 – 2019
- 2019
- [i6]Oleksandr Shchur, Marin Bilos, Stephan Günnemann:
Intensity-Free Learning of Temporal Point Processes. CoRR abs/1909.12127 (2019) - [i5]Oleksandr Shchur, Stephan Günnemann:
Overlapping Community Detection with Graph Neural Networks. CoRR abs/1909.12201 (2019) - 2018
- [c2]Oleksandr Shchur, Aleksandar Bojchevski, Mohamed Farghal, Stephan Günnemann, Yusuf Saber:
Anomaly Detection in Car-Booking Graphs. ICDM Workshops 2018: 604-607 - [c1]Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann:
NetGAN: Generating Graphs via Random Walks. ICML 2018: 609-618 - [i4]Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann:
NetGAN: Generating Graphs via Random Walks. CoRR abs/1803.00816 (2018) - [i3]Federico Monti, Oleksandr Shchur, Aleksandar Bojchevski, Or Litany, Stephan Günnemann, Michael M. Bronstein:
Dual-Primal Graph Convolutional Networks. CoRR abs/1806.00770 (2018) - [i2]Oleksandr Shchur, Maximilian Mumme, Aleksandar Bojchevski, Stephan Günnemann:
Pitfalls of Graph Neural Network Evaluation. CoRR abs/1811.05868 (2018) - 2017
- [i1]Stephan Rabanser, Oleksandr Shchur, Stephan Günnemann:
Introduction to Tensor Decompositions and their Applications in Machine Learning. CoRR abs/1711.10781 (2017)
Coauthor Index
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