Davide Buffelli

24 papers A* 5B 1Journal 16Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Group Think: Multiple Concurrent Reasoning Agents Collaborating at Token Level Granularity. CoRR Chan-Jan Hsu, Davide Buffelli, Jamie McGowan, Feng-Ting Liao, Yi-Chang Chen, Sattar Vakili, Da-Shan Shiu
2025	J	`jnl`	LGDC: Latent Graph Diffusion via Spectrum-Preserving Coarsening. CoRR Nagham Osman, Keyue Jiang, Davide Buffelli, Xiaowen Dong, Laura Toni
2025	J	`jnl`	Towards a Foundation Model for Communication Systems. CoRR Davide Buffelli, Sowmen Das, Yu-Wei Lin, Sattar Vakili, Chien-Yi Wang, Masoud Attarifar, Pritthijit Nath, Da-Shan Shiu
2024	—	`conf`	CliquePH: Higher-Order Information for Graph Neural Networks Through Persistent Homology on Clique Graphs. LoG Davide Buffelli, Farzin Soleymani, Bastian Rieck
2024	J	`jnl`	CliquePH: Higher-Order Information for Graph Neural Networks through Persistent Homology on Clique Graphs. CoRR Davide Buffelli, Farzin Soleymani, Bastian Rieck
2024	A*	`conf`	Deep Equilibrium Algorithmic Reasoning. NeurIPS Dobrik Georgiev, Joseph Wilson, Davide Buffelli, Pietro Lió
2024	J	`jnl`	Deep Equilibrium Algorithmic Reasoning. CoRR Dobrik Georgiev, JJ Wilson, Davide Buffelli, Pietro Liò
2024	A*	`conf`	Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization. NeurIPS Davide Buffelli, Jamie McGowan, Wangkun Xu, Alexandru Cioba, Da-Shan Shiu, Guillaume Hennequin, Alberto Bernacchia
2024	J	`jnl`	Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization. CoRR Davide Buffelli, Jamie McGowan, Wangkun Xu, Alexandru Cioba, Da-Shan Shiu, Guillaume Hennequin, Alberto Bernacchia
2024	J	`jnl`	The Deep Equilibrium Algorithmic Reasoner. CoRR Dobrik Georgiev, Pietro Liò, Davide Buffelli
2023	—	`—`	Improving the Effectiveness of Graph Neural Networks in Practical Scenarios. Davide Buffelli
2023	J	`jnl`	Is Meta-Learning the Right Approach for the Cold-Start Problem in Recommender Systems? CoRR Davide Buffelli, Ashish Gupta, Agnieszka Strzalka, Vassilis Plachouras
2023	A*	`conf`	Scalable Theory-Driven Regularization of Scene Graph Generation Models. AAAI Davide Buffelli, Efthymia Tsamoura
2022	A*	`conf`	Extending Logic Explained Networks to Text Classification. EMNLP Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Davide Buffelli, Pietro Liò
2022	J	`jnl`	Extending Logic Explained Networks to Text Classification. CoRR Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Davide Buffelli, Pietro Liò
2022	B	`conf`	Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach. IJCNN Davide Buffelli, Fabio Vandin
2022	J	`jnl`	Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach. CoRR Davide Buffelli, Fabio Vandin
2022	J	`jnl`	Scalable Regularization of Scene Graph Generation Models using Symbolic Theories. CoRR Davide Buffelli, Efthymia Tsamoura
2022	A*	`conf`	SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks. NeurIPS Davide Buffelli, Pietro Lió, Fabio Vandin
2022	J	`jnl`	SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks. CoRR Davide Buffelli, Pietro Liò, Fabio Vandin
2022	J	`jnl`	The Impact of Global Structural Information in Graph Neural Networks Applications. Data Davide Buffelli, Fabio Vandin
2020	J	`jnl`	A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings. CoRR Davide Buffelli, Fabio Vandin
2020	J	`jnl`	Are Graph Convolutional Networks Fully Exploiting Graph Structure? CoRR Davide Buffelli, Fabio Vandin
2020	J	`jnl`	Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation. CoRR Davide Buffelli, Fabio Vandin