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ORCIDGustav Sír
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- affiliation: Czech Technical University in Prague, Czech Republic
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2020 – today
- 2026
[i18]Danial Hooshyar, Gustav Sír, Yeongwook Yang, Tommi Kärkkäinen, Raija Hämäläinen, Ekaterina Krivich, Mutlu Cukurova, Dragan Gasevic, Roger Azevedo:
Neural-Symbolic Knowledge Tracing: Injecting Educational Knowledge into Deep Learning for Responsible Learner Modelling. CoRR abs/2604.08263 (2026)- 2025
- [j7]Danial Hooshyar
, Gustav Sír, Yeongwook Yang, Eve Kikas, Raija Hämäläinen, Tommi Kärkkäinen, Dragan Gasevic, Roger Azevedo:
Towards responsible AI for education: Hybrid human-AI to confront the elephant in the room. Comput. Educ. Artif. Intell. 9: 100524 (2025) - [j6]Jakub Peleska, Gustav Sír:
Tabular Transformers Meet Relational Databases. ACM Trans. Intell. Syst. Technol. 16(5): 115:1-115:24 (2025) - [j5]Martin Krutsky, Gustav Sír:
Geometric Deep Learning for the Rubik's Cube Group. IEEE Trans. Neural Networks Learn. Syst. 36(12): 20214-20228 (2025) - [c19]Rostislav Horcík, Gustav Sír, Vítezslav Simek, Tomás Pevný:
State Encodings for GNN-Based Lifted Planners. AAAI 2025: 26525-26533 - [c18]Martin Krutsky, Gustav Sír, Vyacheslav Kungurtsev, Georgios Korpas:
Binarizing Physics-Inspired GNNs for Combinatorial Optimization. ECAI 2025: 2017-2024 - [c17]Jakub Peleska, Gustav Sír:
ReDeLEx: A Framework for Relational Deep Learning Exploration. ECML/PKDD (2) 2025: 438-456 - [c16]Jakub Peleska, Gustav Sír:
Task-Agnostic Contrastive Pretraining for Relational Deep Learning. PKDD/ECML Workshops (3) 2025: 623-638 - [c15]Martin Krutsky, Jiri Nemecek, Jakub Peleska, Paula Gürtler, Gustav Sír:
XAI Desiderata for Trustworthy AI: Insights from the AI Act. TRUST-AI@ECAI 2025: 180-187 - [i17]Vyacheslav Kungurtsev, Leonardo Christov Moore, Gustav Sír, Martin Krutsky:
"Cause" is Mechanistic Narrative within Scientific Domains: An Ordinary Language Philosophical Critique of "Causal Machine Learning". CoRR abs/2501.05844 (2025) - [i16]Danial Hooshyar, Eve Kikas, Yeongwook Yang, Gustav Sír, Raija Hämäläinen, Tommi Kärkkäinen, Roger Azevedo:
Towards Responsible and Trustworthy Educational Data Mining: Comparing Symbolic, Sub-Symbolic, and Neural-Symbolic AI Methods. CoRR abs/2504.00615 (2025) - [i15]Danial Hooshyar, Gustav Sír, Yeongwook Yang, Eve Kikas, Raija Hämäläinen, Tommi Kärkkäinen, Dragan Gasevic, Roger Azevedo:
Towards responsible AI for education: Hybrid human-AI to confront the Elephant in the room. CoRR abs/2504.16148 (2025) - [i14]Jakub Peleska, Gustav Sír:
REDELEX: A Framework for Relational Deep Learning Exploration. CoRR abs/2506.22199 (2025) - [i13]Jakub Peleska, Gustav Sír:
Task-Agnostic Contrastive Pretraining for Relational Deep Learning. CoRR abs/2506.22530 (2025) - [i12]Vyacheslav Kungurtsev, Gustav Sír, Akhil S. Anand, Sebastien Gros, Haozhe Tian, Homayoun Hamedmoghadam:
Mission-Aligned Learning-Informed Control of Autonomous Systems: Formulation and Foundations. CoRR abs/2507.04356 (2025) - [i11]Martin Krutsky, Gustav Sír, Vyacheslav Kungurtsev, Georgios Korpas:
Binarizing Physics-Inspired GNNs for Combinatorial Optimization. CoRR abs/2507.13703 (2025) - [i10]Danial Hooshyar, Yeongwook Yang, Gustav Sír, Tommi Kärkkäinen, Raija Hämäläinen, Mutlu Cukurova, Roger Azevedo:
Problems With Large Language Models for Learner Modelling: Why LLMs Alone Fall Short for Responsible Tutoring in K-12 Education. CoRR abs/2512.23036 (2025) - 2024
- [c14]Rostislav Horcík, Gustav Sír:
Expressiveness of Graph Neural Networks in Planning Domains. ICAPS 2024: 281-289 - [i9]Dillon Z. Chen, Rostislav Horcík, Gustav Sír:
Deep Learning for Generalised Planning with Background Knowledge. CoRR abs/2410.07923 (2024) - [i8]Jakub Peleska, Gustav Sír:
Transformers Meet Relational Databases. CoRR abs/2412.05218 (2024) - 2023
- [p1]Gustav Sír, Filip Zelezný, Ondrej Kuzelka:
Lifted Relational Neural Networks: From Graphs to Deep Relational Learning. Compendium of Neurosymbolic Artificial Intelligence 2023: 308-336 - 2022
- [b1]Gustav Sír:
Deep Learning with Relational Logic Representations. Frontiers in Artificial Intelligence and Applications 357, IOS Press 2022, ISBN 978-1-64368-342-3, pp. 1-221 - 2021
- [j4]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Beyond graph neural networks with lifted relational neural networks. Mach. Learn. 110(7): 1695-1738 (2021) - [c13]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Lossless Compression of Structured Convolutional Models via Lifting. ICLR 2021 - [i7]Matej Uhrín, Gustav Sourek, Ondrej Hubácek, Filip Zelezný:
Optimal sports betting strategies in practice: an experimental review. CoRR abs/2107.08827 (2021) - 2020
- [i6]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Beyond Graph Neural Networks with Lifted Relational Neural Networks. CoRR abs/2007.06286 (2020) - [i5]Gustav Sourek, Filip Zelezný:
Lossless Compression of Structured Convolutional Models via Lifting. CoRR abs/2007.06567 (2020) - [i4]Ondrej Hubácek, Gustav Sír:
Beating the market with a bad predictive model. CoRR abs/2010.12508 (2020) - [i3]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Learning with Molecules beyond Graph Neural Networks. CoRR abs/2011.03488 (2020)
2010 – 2019
- 2019
- [j3]Ondrej Hubácek, Gustav Sourek, Filip Zelezný:
Learning to predict soccer results from relational data with gradient boosted trees. Mach. Learn. 108(1): 29-47 (2019) - [j2]Gustav Sourek, Filip Zelezný:
Efficient Extraction of Network Event Types from NetFlows. Secur. Commun. Networks 2019: 8954914:1-8954914:18 (2019) - [c12]Gustav Sourek:
Deep Learning with Relational Logic Representations. IJCAI 2019: 6462-6463 - [c11]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Scaling up relational templated neural models. NeSy@IJCAI 2019 - [c10]Martin Svatos, Gustav Sourek, Filip Zelezný:
Revisiting Neural-Symbolic Learning Cycle. NeSy@IJCAI 2019 - 2018
- [j1]Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Lifted Relational Neural Networks: Efficient Learning of Latent Relational Structures. J. Artif. Intell. Res. 62: 69-100 (2018) - [c9]Ondrej Hubácek, Gustav Sourek, Filip Zelezný:
Lifted Relational Team Embeddings for Predictive Sports Analytics. ILP Up-and-Coming / Short Papers 2018: 84-91 - [c8]Ondrej Hubácek, Gustav Sourek, Filip Zelezný:
Deep Learning from Spatial Relations for Soccer Pass Prediction. MLSA@PKDD/ECML 2018: 159-166 - 2017
- [c7]Gustav Sourek, Martin Svatos, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Stacked Structure Learning for Lifted Relational Neural Networks. ILP 2017: 140-151 - [c6]Martin Svatos, Gustav Sourek, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Pruning Hypothesis Spaces Using Learned Domain Theories. ILP 2017: 152-168 - [i2]Gustav Sourek, Martin Svatos, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Stacked Structure Learning for Lifted Relational Neural Networks. CoRR abs/1710.02221 (2017) - 2016
- [c5]Gustav Sourek, Suresh Manandhar, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Learning Predictive Categories Using Lifted Relational Neural Networks. ILP 2016: 108-119 - 2015
- [c4]Gustav Sourek, Ondrej Kuzelka, Filip Zelezný:
Learning to Detect Network Intrusion from a Few Labeled Events and Background Traffic. AIMS 2015: 73-86 - [c3]Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Ondrej Kuzelka:
Lifted Relational Neural Networks. CoCo@NIPS 2015 - [c2]Gustav Sourek, Petr Posik:
Visual data-flow framework of evolutionary computation. RACS 2015: 343-348 - [i1]Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Ondrej Kuzelka:
Lifted Relational Neural Networks. CoRR abs/1508.05128 (2015) - 2013
- [c1]Gustav Sourek, Ondrej Kuzelka, Filip Zelezný:
Predicting Top-k Trends on Twitter using Graphlets and Time Features. ILP (Late Breaking Papers) 2013: 52-57
Coauthor Index
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