引用次数
引用: 141
H-指数: 6
I10-指数 : 3
出版物: 13
A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings.
Fabio Vandin , Davide Buffelli
arXiv: Learning
8
2020
Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation
Fabio Vandin , Davide Buffelli
IEEE Sensors Journal 1 -1
2021
Scalable theory-driven regularization of scene graph generation models
Davide Buffelli , Efthymia Tsamoura
Proceedings of the AAAI Conference on Artificial Intelligence 37 ( 6) 6850 -6859
4
2023
Scalable regularization of scene graph generation models using symbolic theories
Davide Buffelli , Efthymia Tsamoura
arXiv preprint arXiv:2209.02749
2
2022
Method and system for scene graph generation
Efthymia Tsamoura , Davide Buffelli
2022
Sizeshiftreg: a regularization method for improving size-generalization in graph neural networks
Davide Buffelli , Pietro Liò , Fabio Vandin
Advances in Neural Information Processing Systems 35 31871 -31885
41
2022
Extending logic explained networks to text classification
Rishabh Jain , Gabriele Ciravegna , Pietro Barbiero , Francesco Giannini
arXiv preprint arXiv:2211.09732
9
2022
The Deep Equilibrium Algorithmic Reasoner
Dobrik Georgiev , Pietro Liò , Davide Buffelli
arXiv preprint arXiv:2402.06445
2024
Graph representation learning for multi-task settings: a meta-learning approach
Davide Buffelli , Fabio Vandin
2022 International Joint Conference on Neural Networks (IJCNN) 1 -8
8
2022
The impact of global structural information in graph neural networks applications
Davide Buffelli , Fabio Vandin
Data 7 ( 1) 10 -10
7
2022
Is meta-learning the right approach for the cold-start problem in recommender systems?
Davide Buffelli , Ashish Gupta , Agnieszka Strzalka , Vassilis Plachouras
arXiv preprint arXiv:2308.08354
1
2023
Improving the Effectiveness of Graph Neural Networks in Practical Scenarios
Davide Buffelli
Università degli studi di Padova
2023