Federico Barbero

@UCPSicHM25H1i7u91C8-AdAA - 1.8K subscribers

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How powerful are Graph Neural Networks? - Oxford Geometric Deep Learning

How powerful are Graph Neural Networks? - Oxford Geometric Deep Learning Federico Barbero

2.1K views - 3 years ago

Transformers are Graph Attention Networks !? - Oxford Geometric Deep Learning

Transformers are Graph Attention Networks !? - Oxford Geometric Deep Learning Federico Barbero

5.3K views - 3 years ago

Graph Attention Networks - Oxford Geometric Deep Learning

Graph Attention Networks - Oxford Geometric Deep Learning Federico Barbero

4.9K views - 3 years ago

Graph Convolutional Networks - Oxford Geometric Deep Learning

Graph Convolutional Networks - Oxford Geometric Deep Learning Federico Barbero

17.6K views - 3 years ago

Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift

Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift Federico Barbero

282 views - 3 years ago

Deconstructing the Python Walrus Operator

Deconstructing the Python Walrus Operator Federico Barbero

401 views - 5 years ago

Generators in Python: What are they and their advantages!

Generators in Python: What are they and their advantages! Federico Barbero

334 views - 5 years ago

Why Python list comprehensions are faster and more elegant

Why Python list comprehensions are faster and more elegant Federico Barbero

1.8K views - 5 years ago

Improving your Python by understanding Python bytecode!

Improving your Python by understanding Python bytecode! Federico Barbero

4.8K views - 5 years ago

Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations

Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations Federico Barbero

962 views - 5 years ago

Tempered Sigmoid Activations for Deep Learning with Differential Privacy

Tempered Sigmoid Activations for Deep Learning with Differential Privacy Federico Barbero

349 views - 5 years ago

Regularisation of Neural Networks by Enforcing Lipschitz Continuity

Regularisation of Neural Networks by Enforcing Lipschitz Continuity Federico Barbero

1.7K views - 5 years ago

Spectral Norm Regularization for Improving the Generalizability of Deep Learning

Spectral Norm Regularization for Improving the Generalizability of Deep Learning Federico Barbero

2.6K views - 5 years ago

Developing a Deep Learning Library - LeCun's MNIST classifier - Part 3

Developing a Deep Learning Library - LeCun's MNIST classifier - Part 3 Federico Barbero

398 views - 5 years ago

Developing a Deep Learning Library - Adam, RELU and Scikit-learn API - Part 2

Developing a Deep Learning Library - Adam, RELU and Scikit-learn API - Part 2 Federico Barbero

307 views - 5 years ago

Developing a Deep Learning Library - JoelNet Library and Neural Networks - Part 1

Developing a Deep Learning Library - JoelNet Library and Neural Networks - Part 1 Federico Barbero

510 views - 5 years ago

Tutorial on the Fast Gradient Sign Method for Adversarial Samples

Tutorial on the Fast Gradient Sign Method for Adversarial Samples Federico Barbero

10.4K views - 5 years ago

Lipschitz Regularization of Neural Networks - Intriguing Properties of Neural Networks

Lipschitz Regularization of Neural Networks - Intriguing Properties of Neural Networks Federico Barbero

2.5K views - 5 years ago

What are Adversarial Samples in Machine Learning? - Explaining and Harnessing Adversarial Samples

What are Adversarial Samples in Machine Learning? - Explaining and Harnessing Adversarial Samples Federico Barbero

3.9K views - 5 years ago