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Advancing digital twins research: Experts explore Bayesian inference, irregular posteriors, and geophysical applications in this foundational workshop for data-driven engineering.
Explore the impact of Large Language Models on scientific research and publishing, discussing challenges, opportunities, and future implications for the field.
Exploring governance of large AI models, examining unique features, legal issues, and the EU AI Act's risk-based approach. Expert panel discusses ethical and regulatory challenges.
Explore emerging display and interaction technologies for data visualization, focusing on immersive analytics and embodied sensemaking techniques to enhance data understanding and analysis.
Discover "glue," a powerful analysis/visualization tool for exploring diverse datasets across fields. Learn its origins, capabilities, and applications in astronomy, genomics, and beyond.
Explore Vega's ecosystem of declarative visualization languages and interactive tools for creating rich, interactive visualizations with layered abstractions and flexible designs.
Explores theoretical analysis of denoising diffusion models, providing convergence results for data distributions on lower-dimensional manifolds or empirical distributions, with quantitative bounds on Wasserstein distance.
Explore advanced Langevin Monte Carlo techniques, focusing on the Randomized Midpoint method's superior sampling error guarantees and recent improvements for high-dimensional target distributions.
Explore advanced generative modeling techniques, from denoising diffusion models to transport-based approaches, focusing on diffusion Schrödinger bridge and its numerical approximation for improved inference.
Exploring advances in probabilistic emulators for parametric PDEs, including boundary condition enforcement and Random Grid Neural Processes for efficient engineering problem-solving.
Explore a novel interacting particle system for EM optimization in latent variable models, featuring Langevin diffusion analysis and non-asymptotic concentration bounds for maximum likelihood estimation.
Explore collaborative historical research in the digital age, discussing challenges, methodologies, and lessons learned from the "Living with Machines" project and its impact on 19th-century British history.
Explore clinical AI applications in healthcare with experts, covering interest groups, supra-interest groups, and ensuring safe, effective, and equitable AI implementation in health.
Explore causal effect identification using do-calculus search algorithms, addressing complex data scenarios like missing data and context-specific independence in causal inference.
Dive into the world of foundation models with experts Anthony Cohn and Yarin Gal, exploring cutting-edge developments and implications in artificial intelligence.
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