Juan Cerviño

4 papers · 2022–2025 · 3 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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🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (11) 🐣 Hot Topic Early Bird

Venues

ICML (2) AAAI (1) ICLR (1)

Top co-authors

Alejandro Ribeiro (4) Zhiyang Wang (2) Benjamin David Haeffele (1) Hamed Hassani (1) Luiz F. O. Chamon (1) Zebang Shen (1) René Vidal (1)

Research topics

Machine Learning (4) Optimization & Theory · Machine Learning (3) Deep Learning (2) Architectures (2) Core Methods (2) Artificial Intelligence (1) Mathematics & Optimization (1) Application Areas (1) Learning Paradigms (1) Mathematics (1) Optimization & Theory · Deep Learning (1)

Keywords

graph neural network (2) representation learning (1) manifold learning (1) manifold regularization (1) model robustness (1) class imbalance (1) agnostic learning (1) distribution shift (1) lipschitz continuity (1) generalization bound (1) data heterogeneity (1) generalization theory (1) weighted laplacian penalty (1) stochastic gradient technique (1) filter function (1) spectral domain (1) geometric graph (1) model mismatch (1) manifold (1) federated learning (1)

Papers

A Manifold Perspective on the Statistical Generalization of Graph Neural Networks ICML 2025 Generalization of Graph Neural Networks Is Robust to Model Mismatch AAAI 2025 Learning Globally Smooth Functions on Manifolds ICML 2023 An Agnostic Approach to Federated Learning with Class Imbalance ICLR 2022