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Graph Representation Learning for Multi-Task Settings: a Meta-Learning
  Approach

Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach

10 January 2022
Davide Buffelli
Fabio Vandin
    AI4CE
ArXivPDFHTML

Papers citing "Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach"

13 / 13 papers shown
Title
Neural Relational Inference with Fast Modular Meta-learning
Neural Relational Inference with Fast Modular Meta-learning
Ferran Alet
Erica Weng
Tomás Lozano Pérez
L. Kaelbling
92
56
0
10 Oct 2023
In Defense of the Unitary Scalarization for Deep Multi-Task Learning
In Defense of the Unitary Scalarization for Deep Multi-Task Learning
Vitaly Kurin
Alessandro De Palma
Ilya Kostrikov
Shimon Whiteson
M. P. Kumar
56
75
0
11 Jan 2022
TUDataset: A collection of benchmark datasets for learning with graphs
TUDataset: A collection of benchmark datasets for learning with graphs
Christopher Morris
Nils M. Kriege
Franka Bause
Kristian Kersting
Petra Mutzel
Marion Neumann
111
802
0
16 Jul 2020
Meta-Learning in Neural Networks: A Survey
Meta-Learning in Neural Networks: A Survey
Timothy M. Hospedales
Antreas Antoniou
P. Micaelli
Amos Storkey
OOD
258
1,950
0
11 Apr 2020
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness
  of MAML
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
Aniruddh Raghu
M. Raghu
Samy Bengio
Oriol Vinyals
293
641
0
19 Sep 2019
Which Tasks Should Be Learned Together in Multi-task Learning?
Which Tasks Should Be Learned Together in Multi-task Learning?
Trevor Scott Standley
Amir Zamir
Dawn Chen
Leonidas Guibas
Jitendra Malik
Silvio Savarese
66
509
0
18 May 2019
Edge-labeling Graph Neural Network for Few-shot Learning
Edge-labeling Graph Neural Network for Few-shot Learning
Jongmin Kim
Taesup Kim
Sungwoong Kim
Chang D. Yoo
47
455
0
04 May 2019
Adversarial Attacks on Graph Neural Networks via Meta Learning
Adversarial Attacks on Graph Neural Networks via Meta Learning
Daniel Zügner
Stephan Günnemann
OOD
AAML
GNN
101
569
0
22 Feb 2019
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
115
7,554
0
01 Oct 2018
Few-Shot Learning with Graph Neural Networks
Few-Shot Learning with Graph Neural Networks
Victor Garcia Satorras
Joan Bruna
GNN
138
1,235
0
10 Nov 2017
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry
  and Semantics
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics
Alex Kendall
Y. Gal
R. Cipolla
3DH
171
3,093
0
19 May 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
735
11,793
0
09 Mar 2017
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
422
3,264
0
24 Nov 2016
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