Juan Cerviño - RankMe

34 papers A* 5C 1Misc 3Journal 22Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Position: Message-passing and spectral GNNs are two sides of the same coin. CoRR Antonis Vasileiou, Juan Cerviño, Pascal Frossard, Charilaos I. Kanatsoulis, Christopher Morris, Michael T. Schaub, Pierre Vandergheynst, Zhiyang Wang, Guy Wolf, Ron Levie
2025	A*	`conf`	A Manifold Perspective on the Statistical Generalization of Graph Neural Networks. ICML Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro
2025	A*	`conf`	Constrained Learning for Decentralized Multi-Objective Coverage Control. ICRA Juan Cerviño, Saurav Agarwal, Vijay Kumar, Alejandro Ribeiro
2025	J	`jnl`	Cross-Learning from Scarce Data via Multi-Task Constrained Optimization. CoRR Leopoldo Agorio, Juan Cerviño, Miguel Calvo-Fullana, Alejandro Ribeiro, Juan Andrés Bazerque
2025	J	`jnl`	Distributed Training of Large Graph Neural Networks With Variable Communication Rates. IEEE Trans. Signal Inf. Process. over Networks Juan Cerviño, Md Asadullah Turja, Hesham Mostafa, Nageen Himayat, Alejandro Ribeiro
2025	J	`jnl`	Generalization of Geometric Graph Neural Networks With Lipschitz Loss Functions. IEEE Trans. Signal Process. Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro
2025	A*	`conf`	Generalization of Graph Neural Networks Is Robust to Model Mismatch. AAAI Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro
2024	J	`jnl`	A Manifold Perspective on the Statistical Generalization of Graph Neural Networks. CoRR Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro
2024	J	`jnl`	Constrained Learning for Decentralized Multi-Objective Coverage Control. CoRR Juan Cerviño, Saurav Agarwal, Vijay Kumar, Alejandro Ribeiro
2024	J	`jnl`	Distributed Training of Large Graph Neural Networks with Variable Communication Rates. CoRR Juan Cerviño, Md Asadullah Turja, Hesham Mostafa, Nageen Himayat, Alejandro Ribeiro
2024	J	`jnl`	Generalization of Geometric Graph Neural Networks. CoRR Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro
2024	J	`jnl`	Generalization of Graph Neural Networks is Robust to Model Mismatch. CoRR Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro
2024	—	`conf`	Generalization of Graph Neural Networks: Over Geometric Graphs Sampled from Manifolds. IEEECONF Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro
2023	J	`jnl`	FastSample: Accelerating Distributed Graph Neural Network Training for Billion-Scale Graphs. CoRR Hesham Mostafa, Adam Grabowski, Md Asadullah Turja, Juan Cerviño, Alejandro Ribeiro, Nageen Himayat
2023	—	`conf`	Intrinsically Motivated Graph Exploration Using Network Theories of Human Curiosity. LoG Shubhankar Prashant Patankar, Mathieu Ouellet, Juan Cerviño, Alejandro Ribeiro, Kieran A. Murphy, Danielle S. Bassett
2023	J	`jnl`	Intrinsically motivated graph exploration using network theories of human curiosity. CoRR Shubhankar P. Patankar, Mathieu Ouellet, Juan Cerviño, Alejandro Ribeiro, Kieran A. Murphy, Dani S. Bassett
2023	A*	`conf`	Learning Globally Smooth Functions on Manifolds. ICML Juan Cerviño, Luiz F. O. Chamon, Benjamin David Haeffele, René Vidal, Alejandro Ribeiro
2023	J	`jnl`	Learning by Transference: Training Graph Neural Networks on Growing Graphs. IEEE Trans. Signal Process. Juan Cerviño, Luana Ruiz, Alejandro Ribeiro
2023	Misc	`conf`	Multi-Task Bias-Variance Trade-Off Through Functional Constraints. ICASSP Juan Cerviño, Juan Andrés Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro
2023	Misc	`conf`	Training Graph Neural Networks on Growing Stochastic Graphs. ICASSP Juan Cerviño, Luana Ruiz, Alejandro Ribeiro
2022	A*	`conf`	An Agnostic Approach to Federated Learning with Class Imbalance. ICLR Zebang Shen, Juan Cerviño, Hamed Hassani, Alejandro Ribeiro
2022	J	`jnl`	Federated Representation Learning via Maximal Coding Rate Reduction. CoRR Juan Cerviño, Navid Naderializadeh, Alejandro Ribeiro
2022	J	`jnl`	Learning Globally Smooth Functions on Manifolds. CoRR Juan Cerviño, Luiz F. O. Chamon, Benjamin D. Haeffele, René Vidal, Alejandro Ribeiro
2022	J	`jnl`	Multi-task Bias-Variance Trade-off Through Functional Constraints. CoRR Juan Cerviño, Juan Andrés Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro
2022	J	`jnl`	Training Graph Neural Networks on Growing Stochastic Graphs. CoRR Juan Cerviño, Luana Ruiz, Alejandro Ribeiro
2022	Misc	`conf`	Training Stable Graph Neural Networks Through Constrained Learning. ICASSP Juan Cerviño, Luana Ruiz, Alejandro Ribeiro
2021	J	`jnl`	Increase and Conquer: Training Graph Neural Networks on Growing Graphs. CoRR Juan Cerviño, Luana Ruiz, Alejandro Ribeiro
2021	J	`jnl`	Multi-Task Reinforcement Learning in Reproducing Kernel Hilbert Spaces via Cross-Learning. IEEE Trans. Signal Process. Juan Cerviño, Juan Andrés Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro
2021	—	`conf`	Multi-task Supervised Learning via Cross-learning. EUSIPCO Juan Cerviño, Juan Andrés Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro
2021	J	`jnl`	Training Stable Graph Neural Networks Through Constrained Learning. CoRR Juan Cerviño, Luana Ruiz, Alejandro Ribeiro
2020	J	`jnl`	Multi-task Reinforcement Learning in Reproducing Kernel Hilbert Spaces via Cross-learning. CoRR Juan Cerviño, Juan Andrés Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro
2020	J	`jnl`	Multi-task Supervised Learning via Cross-learning. CoRR Juan Cerviño, Juan Andrés Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro
2020	J	`jnl`	Parameter Critic: a Model Free Variance Reduction Method Through Imperishable Samples. CoRR Juan Cerviño, Harshat Kumar, Alejandro Ribeiro
2019	C	`conf`	Meta-Learning through Coupled Optimization in Reproducing Kernel Hilbert Spaces. ACC Juan Cerviño, Juan Andrés Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro