Anastasis Kratsios

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Ivan DokmanićAssociate Professor, Department of Mathematics and Computer Science, University of BaselVerified email at illinois.edu
Maarten de HoopRice UniversityVerified email at rice.edu
Takashi FuruyaShimane UniversityVerified email at riko.shimane-u.ac.jp
Gudmund PammerETH ZurichVerified email at math.ethz.ch
Haitz Sáez de Ocáriz BordeUniversity of OxfordVerified email at cam.ac.uk
Aurelien LucchiAssistant Professor, Department of Mathematics and Computer Science, University of BaselVerified email at inf.ethz.ch
Behnoosh ZamanlooyPhD Researcher in Computer Science, McMaster UniversityVerified email at mcmaster.ca
Beatrice AcciaioProfessor, ETH ZurichVerified email at math.ethz.ch
Florian KrachDoctoral Student in Mathematics, ETH ZürichVerified email at math.ethz.ch
Matti LassasProfessor of applied mathematics, University of Helsinki, FinlandVerified email at helsinki.fi
Luca GalimbertiKing's College LondonVerified email at kcl.ac.uk
Giulia LivieriVerified email at sns.it
Josef TeichmannETH ZurichVerified email at math.ethz.ch
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
Jonas RothfussResearch Scientist @ Google DeepMindVerified email at google.com
Michael BronsteinDeepMind Professor of AI, University of Oxford / Scientific Director, AITHYRAVerified email at cs.ox.ac.uk
Alexander KorotinSkoltech, AIRIVerified email at skoltech.ru
Evgeny BurnaevSkoltech, Full Professor, Head of Applied AI center, Head of research group, AIRIVerified email at skoltech.ru
John ArmstrongKing's College LondonVerified email at kcl.ac.uk
ibrahim ekrenUniversity of MichiganVerified email at umich.edu

Anastasis Kratsios

McMaster University and Vector Institute

Verified email at mcmaster.ca - Homepage

Deep Learning Theory Geometric Deep Learning Computational Finance Learning Theory


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
The Universal Approximation Property A Kratsios Annals of Mathematics and Artificial Intelligence, 2021	112*	2021
Non-Euclidean Universal Approximation A Kratsios, E Bilokopytov Advances in Neural Information Processing Systems 33, 10635--10646, 2020	83	2020
Universal Approximation Theorems for Differentiable Geometric Deep Learning A Kratsios, L Papon Journal of Machine Learning Research 23 (196), 1-73, 2022	43*	2022
Neu: A Meta-Algorithm for Universal UAP-Invariant Feature Representation A Kratsios, C Hyndman The Journal of Machine Learning Research 22 (1), 4102-4152, 2021	37	2021
Designing Universal Causal Deep Learning Models: The Geometric (Hyper) Transformer B Acciaio, A Kratsios, G Pammer Mathematical Finance, 2023	35*	2023
Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equation JAL Benitez, T Furuya, F Faucher, A Kratsios, X Tricoche, MV de Hoop Journal of Computational Physics, 113168, 2024	28*	2024
Universal Approximation Under Constraints is Possible with Transformers A Kratsios, B Zamanlooy, I Dokmanić, T Liu International Conference on Learning Representations (ICLR) 10, 2022	27	2022
Deep arbitrage-free learning in a generalized HJM framework via arbitrage-regularization A Kratsios, C Hyndman Risks 8 (2), 40, 2020	19*	2020
Designing universal causal deep learning models: The case of infinite-dimensional dynamical systems from stochastic analysis L Galimberti, A Kratsios, G Livieri arXiv preprint arXiv:2210.13300, 2022	16	2022
Small Transformers Compute Universal Metric Embeddings A Kratsios, V Debarnot, I Dokmanić Journal of Machine Learning Research (JMLR), 2023	13	2023
Instance-dependent generalization bounds via optimal transport S Hou, P Kassraie, A Kratsios, A Krause, J Rothfuss Journal of Machine Learning Research, 2023	11	2023
Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices JT C Herrera, F Krach, A Kratsios, P Ruyssen Transactions on Machine Learning Research (TMLR), 2023	11*	2023
Learning Sub-Patterns in Piece-Wise Continuous Functions A Kratsios, B Zamanlooy Neurocomputing 480 (10.1016/j.neucom.2022.01), 192-211, 2022	11	2022
Characterizing overfitting in kernel ridgeless regression through the eigenspectrum TS Cheng, A Lucchi, A Kratsios, D Belius arXiv preprint arXiv:2402.01297, 2024	10	2024
Universal Regular Conditional Distributions via Probabilistic Transformers A Kratsios Constructive Approximation 57 (3), 1145-1212, 2023	9*	2023
Do ReLU Networks Have An Edge When Approximating Compactly-Supported Functions? A Kratsios, B Zamanlooy Transactions on Machine Learning Research 1 (1), 1-21, 2022	8*	2022
A theoretical analysis of the test error of finite-rank kernel ridge regression TS Cheng, A Lucchi, A Kratsios, I Dokmanić, D Belius Advances in Neural Information Processing Systems 36, 4767-4798, 2023	7	2023
Optimizing Optimizers: Regret-optimal gradient descent algorithms P Casgrain, A Kratsios Conference on Learning Theory (COLT) 34, 2021	5	2021
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries HSO Borde, A Kratsios arXiv preprint arXiv:2310.15003, 2023	4*	2023
An Approximation Theory for Metric Space-Valued Functions With A View Towards Deep Learning A Kratsios, C Liu, M Lassas, MV de Hoop, I Dokmanić	3*	2023

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