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R0:c4c3ffc882452ee50fea21d2c6b1486a-CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization

CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization

CNN Explainer tightly integrates a model overview that summarizes a CNN’s structure, and on-demand, dynamic visual explanation views that help users understand the underlying components of CNNs. Through smooth transitions across levels of abstraction, our tool enables users to inspect the interplay between low-level mathematical operations and high-level model structures.

R0:884a5f6297216a3c5e883ae639b13721-Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP

Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP

In this survey, we connect several lines of work from the pre-neural and neural era, by showing how hybrid approaches of words and characters as well as subword-based approaches based on learned segmentation have been proposed and evaluated. We conclude that there is and likely will never be a silver bullet singular solution for all applications and that thinking seriously about tokenization remains important for many applications

R0:8c6cf8db215cbc24a8aec1e0786e1356-AI and the Future of Skills, Volume 1

AI and the Future of Skills, Volume 1

The OECD launched the Artificial Intelligence and the Future of Skills project to develop a programme that could assess the capabilities of AI and robotics and their impact on education and work. This report represents the first step in developing the methodological approach of the project.

R0:0c354476e45d451a73b569693db4f74a-From Zero to Research Scientist full resources guide

From Zero to Research Scientist full resources guide

This guide is designated to anybody with basic programming knowledge or a computer science background interested in becoming a Research Scientist with on Deep Learning and NLP.

Federated Quantum Machine Learning

Federated Quantum Machine Learning

We present the federated training on hybrid quantum-classical machine learning models although our framework could be generalized to pure quantum machine learning model. Specifically, we consider the quantum neural network (QNN) coupled with classical pre-trained convolutional model.