Deep Learning
We have come a long way since the concept of Artificial Intelligence was first discussed in 1950’s, and now enjoy many everyday products and services that rely on it such as digital assistants, personalised recommendations, credit card fraud detection, and improved healthcare treatments.
Deep Learning is a subfield of Machine Learning which focuses on teaching computers to behave like a human brain to process data, create patterns, and make decisions. It does so by employing multiple layers, called neural networks, able to ‘learn’ from large amounts of data. The more a deep learning algorithm performs a task, the better it becomes at it, in the same way we humans learn from past experiences.
Potential topics include but are not limited to:
- Deep neural and belief networks
- Deep reinforcement learning
- Recurrent and convolutional neural networks
- Machine Translation
- Natural Language Processing
- Unsupervised, semi and supervised learning
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Open LetterPeer review process completedAuthors: Sonia Longhi, Salvador Ventura, Sandra Macedo-Ribeiro, Leandro G. Radusky, Jovana Kovačević, R. Gonzalo Parra, Miguel A. Andrade-Navarro, Andrey V. Kajava, Zuzana Bednáriková, Alexander Monzon, Rita VilaçaFunders: COST ActionsPeer reviewers: Judith Bernett, Marcelo Melo, Nicola BordinPublished: July 15, 2025
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Method ArticleRevisedPeer review process completedAuthors: Klaus Schlachter, Kastor Felsner, Sebastian ZambalFunders: Horizon 2020, Societal ChallengesPeer reviewers: Carmelo Mineo, Iikka VIRKKUNENPublished: May 11, 2022