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Oleksandr Shchur
Oleksandr Shchur
Applied Scientist, AWS AI
Verified email at amazon.com - Homepage
Title
Cited by
Cited by
Year
Pitfalls of Graph Neural Network Evaluation
O Shchur, M Mumme, A Bojchevski, S Günnemann
Relational Representation Learning Workshop, NeurIPS 2018, 2018
11252018
NetGAN: Generating Graphs via Random Walks
A Bojchevski, O Shchur, D Zügner, S Günnemann
International Conference on Machine Learning (ICML), 2018
4092018
Introduction to tensor decompositions and their applications in machine learning
S Rabanser, O Shchur, S Günnemann
arXiv preprint arXiv:1711.10781, 2017
2582017
Intensity-Free Learning of Temporal Point Processes
O Shchur, M Biloš, S Günnemann
International Conference on Learning Representations (ICLR), 2020
1482020
Overlapping Community Detection with Graph Neural Networks
O Shchur, S Günnemann
Deep Learning on Graphs Workshop, KDD 2019, 2019
1142019
Dual-primal graph convolutional networks
F Monti, O Shchur, A Bojchevski, O Litany, S Günnemann, MM Bronstein
Graph Embedding and Mining Workshop, ECML-PKDD 2019, 2018
103*2018
Neural Temporal Point Processes: A Review
O Shchur, AC Türkmen, T Januschowski, S Günnemann
International Joint Conference on Artificial Intelligence (IJCAI), 2021
722021
Fast and Flexible Temporal Point Processes with Triangular Maps
O Shchur, N Gao, M Biloš, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2020
262020
Detecting Anomalous Event Sequences with Temporal Point Processes
O Shchur, AC Türkmen, T Januschowski, J Gasthaus, S Günnemann
Neural Information Processing Systems (NeurIPS), 2021
92021
Anomaly detection in car-booking graphs
O Shchur, A Bojchevski, M Farghal, S Günnemann, Y Saber
2018 IEEE International Conference on Data Mining Workshops (ICDMW), 604-607, 2018
72018
Using deep learning for flexible and scalable earthquake forecasting
K Dascher‐Cousineau, O Shchur, EE Brodsky, S Günnemann
Geophysical Research Letters 50 (17), e2023GL103909, 2023
62023
AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting
O Shchur, C Turkmen, N Erickson, H Shen, A Shirkov, T Hu, Y Wang
AutoML Conference, 2023
52023
Add and Thin: Diffusion for Temporal Point Processes
D Lüdke, M Biloš, O Shchur, M Lienen, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2023
22023
Chronos: Learning the Language of Time Series
AF Ansari, L Stella, C Turkmen, X Zhang, P Mercado, H Shen, O Shchur, ...
arXiv preprint arXiv:2403.07815, 2024
12024
Chronos: Learning the Language of Time Series
A Fatir Ansari, L Stella, C Turkmen, X Zhang, P Mercado, H Shen, ...
arXiv e-prints, arXiv: 2403.07815, 2024
2024
Are size and timing within earthquake sequences separable?
K Dascher-Cousineau, B Emily, O Shchur
AGU Fall Meeting Abstracts 2022, S56A-05, 2022
2022
Quantifying Causal Contribution in Rare Event Data
AC Turkmen, D Janzing, O Shchur, L Minorics, L Callot
A causal view on dynamical systems, NeurIPS 2022 workshop, 2022
2022
Modeling Continuous-time Event Data with Neural Temporal Point Processes
O Shchur
Technische Universität München, 2022
2022
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Articles 1–18