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Explore counterfactual prediction in transport modeling, enhancing decision-making capabilities through causal inference and machine learning for 'what if' scenarios and fairness considerations.
Explore cutting-edge machine learning applications in biomedical data interpretation, from cellular analysis to surgical skill assessment, with renowned engineer René Vidal.
Explore state-building, identity, and digital technology's impact on power dynamics and citizen experiences in modern governance systems.
Explore data literacy's importance and the visualization designer's role in effective data comprehension. Learn key aspects of impactful visualizations and industry challenges through real-world examples and expert insights.
Explore machine learning applications in condensed matter physics, from electronic simulations to material engineering. Discover how ML enhances computational methods and enables new physical insights for exotic materials.
Explore real-time data assimilation for digital twins using particle filtering techniques, with interactive demonstrations and discussions on parallelization, future applications, and implementation challenges.
Explore AI explainability principles, biases, and ethical considerations in recruitment through an interactive workshop on practical implementation and fairness.
Deep learning framework for Arctic sea ice forecasting, exploring IceNet's model, pipeline, and ecosystem. Insights into data processing, visualization, and real-world applications.
Explore Equadratures, an open-source platform for model development. Learn about polynomials, variable projection, and applications in this interactive workshop from the Alan Turing Institute.
Explore collaborative research practices, career pathways, and tools in data science through The Turing Way project. Learn about open science, reproducibility, and community-driven knowledge sharing.
Explore real-time graph analytics with Raphtory, covering social networks, time-based graphs, and advanced features like historical properties and query languages.
Explore interpretable machine learning for high-stakes decisions. Learn about optimal scoring systems, their applications in healthcare and criminal justice, and the importance of transparency in AI models.
Explore model-based deep learning for imaging and communications, merging parametric models with optimization tools for efficient, interpretable networks applicable to various real-world problems.
Emmanuel Candes discusses novel calibration techniques for machine learning predictions, addressing issues like false discovery rate control and adaptive conformal inference to handle distribution shifts.
Stuart Russell explores the potential and risks of AI surpassing human capabilities, proposing a fundamental shift in AI development to ensure beneficial outcomes and addressing key ethical and philosophical questions.
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