Self-Supervised Learning: Training AI Models with Less Labels

From Experience to Expertise: An Introduction to Transfer Learning

An accessible introduction to representation learning and interpretability

Hyperspectral Imaging and Machine Learning: Decoding the Spectrum for Advanced Data Analysis

Get familiar with the standard dataset distillation techniques, and gain familiarity with uses cases that could benefit from it.

Twin Network Augmentation for Convolutional Neural Networks.

Explainability-Driven Dimensionality Reduction for Hyperspectral Imaging

A swift introduction to weight-based interpretability.

General presentation about explainability

Analyzing Representations Learned via Capsule Neural Networks. A systematic and principled study towards assessing the interpretability of Capsule networks

Recognizing actions in high-resolution low-framerate videos: a feasibility study in the construction sector.

Presentation on coherence between different evaluation metrics for visual explanations.

General presentation about explainability