OxML 2021

Description

This track builds a strong foundation in core machine learning principles, covering optimisation, classical models, and essential mathematical tools. It equips participants with the theoretical grounding needed to engage with advanced topics across the school.

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Description

This track explores methods for learning meaningful representations from complex, high-dimensional data, including self-supervised and generative approaches. Participants will also dive into probabilistic modelling and uncertainty estimation to better understand and reason about data.

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Description

This track focuses on applying machine learning to biomedical data, clinical decision-making, and real-world healthcare challenges. Participants learn about model evaluation, safety, and translation of AI systems into high-stakes medical settings.

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Description

The NLP track introduces modern language modelling techniques, from traditional embeddings to large-scale transformer architectures. It provides practical insight into how these models understand, generate, and reason with human language.

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Description

This track highlights how AI can be used to address global challenges aligned with the UN SDGs. It showcases applications that promote positive societal impact, with an emphasis on fairness, inclusivity, and responsible deployment.

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