Anastasis Kratsios
15 papers · 2020–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🗺️ Taxonomy Completionist (30) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
🌱
Topic Pioneer
👑
Triple Crown
🏆
Keyword Champion
(4)
💎
Century Club · Bronze
🗃️
Keyword Collector
(82)
🔥
Unstoppable · Bronze
Venues
Top co-authors
Research topics
Machine Learning
(15)
Optimization & Theory · Machine Learning
(11)
Deep Learning
(9)
Architectures
(9)
Core Methods
(7)
Artificial Intelligence
(5)
Mathematics & Optimization
(5)
Core AI
(3)
Optimization
(3)
Bayesian & Probabilistic
(2)
Mathematics
(2)
Optimization & Theory · Deep Learning
(2)
Learning Paradigms
(1)
Techniques
(1)
Keywords
universal approximation
(4)
optimal transport
(2)
kernel ridge regression
(2)
manifold learning
(2)
geometric deep learning
(2)
neural network architecture
(2)
generalization bound
(2)
transfer learning
(1)
neural network theory
(1)
feature learning
(1)
attention mechanism
(1)
probabilistic modeling
(1)
feature representation
(1)
dimension reduction
(1)
gradient descent
(1)
optimal control
(1)
regret minimization
(1)
time series forecasting
(1)
constraint satisfaction
(1)
convex optimization
(1)
Papers
Filtered not Mixed: Filtering-Based Online Gating for Mixture of Large Language Models
ICLR 2025
Neural Operators Can Play Dynamic Stackelberg Games
JMLR 2025
Neural Spacetimes for DAG Representation Learning
ICLR 2025
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression
NeurIPS 2024
Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
ICML 2024
Energy-Guided Continuous Entropic Barycenter Estimation for General Costs
NeurIPS 2024
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries
ICLR 2024
A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression
NeurIPS 2023
Instance-Dependent Generalization Bounds via Optimal Transport
JMLR 2023
Small Transformers Compute Universal Metric Embeddings
JMLR 2023
Universal Approximation Theorems for Differentiable Geometric Deep Learning
JMLR 2022
Universal Approximation Under Constraints is Possible with Transformers
ICLR 2022
NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation
JMLR 2021
Optimizing Optimizers: Regret-optimal gradient descent algorithms
COLT 2021
Non-Euclidean Universal Approximation
NeurIPS 2020