Kratsios, Anastasis

18 publications

TMLR 2025 Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of Experts Anastasis Kratsios, Haitz Sáez de Ocáriz Borde, Takashi Furuya, Marc T. Law

ICLR 2025 Filtered Not Mixed: Filtering-Based Online Gating for Mixture of Large Language Models Raeid Saqur, Anastasis Kratsios, Florian Krach, Yannick Limmer, Blanka Horvath, Frank Rudzicz

ICLRW 2025 Graph Low-Rank Adapters of High Regularity for Graph Neural Networks and Graph Transformers Pantelis Papageorgiou, Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Michael M. Bronstein

ICLR 2025 Neural Spacetimes for DAG Representation Learning Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein

NeurIPS 2024 A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression Tin Sum Cheng, Aurelien Lucchi, Anastasis Kratsios, David Belius

ICML 2024 Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum Tin Sum Cheng, Aurelien Lucchi, Anastasis Kratsios, David Belius

NeurIPS 2024 Energy-Guided Continuous Entropic Barycenter Estimation for General Costs Alexander Kolesov, Petr Mokrov, Igor Udovichenko, Milena Gazdieva, Gudmund Pammer, Anastasis Kratsios, Evgeny Burnaev, Alexander Korotin

ICLR 2024 Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries Haitz Sáez de Ocáriz Borde, Anastasis Kratsios

NeurIPS 2023 A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression Tin Sum Cheng, Aurelien Lucchi, Anastasis Kratsios, Ivan Dokmanić, David Belius

TMLR 2023 Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices Calypso Herrera, Florian Krach, Anastasis Kratsios, Pierre Ruyssen, Josef Teichmann

JMLR 2023 Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou, Parnian Kassraie, Anastasis Kratsios, Andreas Krause, Jonas Rothfuss

JMLR 2023 Small Transformers Compute Universal Metric Embeddings Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanić

TMLR 2022 Do ReLU Networks Have an Edge When Approximating Compactly-Supported Functions? Anastasis Kratsios, Behnoosh Zamanlooy

JMLR 2022 Universal Approximation Theorems for Differentiable Geometric Deep Learning Anastasis Kratsios, Léonie Papon

ICLR 2022 Universal Approximation Under Constraints Is Possible with Transformers Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu, Ivan Dokmanić

JMLR 2021 NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation Anastasis Kratsios, Cody Hyndman

COLT 2021 Optimizing Optimizers: Regret-Optimal Gradient Descent Algorithms Philippe Casgrain, Anastasis Kratsios

NeurIPS 2020 Non-Euclidean Universal Approximation Anastasis Kratsios, Ievgen Bilokopytov