Leonardo Cotta | DeepAI

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∙ 08/08/2023

Probabilistic Invariant Learning with Randomized Linear Classifiers

Designing models that are both expressive and preserve known invariances...

0 Leonardo Cotta, et al. ∙

∙ 02/02/2023

Causal Lifting and Link Prediction

Current state-of-the-art causal models for link prediction assume an und...

1 Leonardo Cotta, et al. ∙

∙ 10/01/2021

Reconstruction for Powerful Graph Representations

Graph neural networks (GNNs) have limited expressive power, failing to r...

12 Leonardo Cotta, et al. ∙

∙ 10/08/2020

Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models

Existing Graph Neural Network (GNN) methods that learn inductive unsuper...

0 Leonardo Cotta, et al. ∙

∙ 09/14/2018

Graph Pattern Mining and Learning through User-defined Relations (Extended Version)

In this work we propose R-GPM, a parallel computing framework for graph ...

0 Carlos H. C. Teixeira, et al. ∙

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