AI is fast becoming a significant consumer of the world’s computational power, so it is crucial to use that power wisely and efficiently. Our approaches to doing so must span all levels of the research stack: from fundamental theoretical understanding of the loss surfaces and regularization properties of machine learning models, to efficient ...

Andrew Fitzgibbon is an Engineering Fellow at Graphcore, working on the future of computing hardware and programming for AI and numerical computing. He is best known for his work on computer vision: he was a core contributor to the Emmy-award-winning 3D camera tracker “boujou”, having co-founded the company “2d3”, with Andrew Zisserman, ...

Learning over graph-structured data is central to a wide range of domains, including social networks, biological systems, and medicine. Graph Neural Networks (GNNs) have emerged as the leading methodology for such tasks, predicated on the assumption that the input graph encodes information relevant to the predictive objective. Nevertheless, there ...

Maya is a Research Scientist at Meta and a last-year Ph.D. candidate in Computer Science at Tel Aviv University, where she is also a Lecturer, teaching "Machine Learning with Graphs." She is a domain expert in Graph Machine Learning, with research spanning both theoretical and applied aspects, including its integration with LLMs and ...

This talk explores how Large Language Models (LLMs) can revolutionize software development by enhancing programmer productivity. We will discuss key applications such as in-IDE code completion and code-assistant chatbots, demonstrating how LLMs can automate tasks and allow developers to focus on high-level design.

Baptiste is leading the code generation team at Mistral AI. Previously, he was a research scientist in the codegen team at Meta AI in Paris working. He contributed to Llama and led Code Llama. During his PhD at Meta AI and Université Paris Dauphine, Baptiste conducted research on unsupervised translation of programming languages and model ...

AI is transforming research information changing our life and the way we work in science, particularly in cardiovascular research. In my talk, I will be presenting several AI-based methods that might help improving the diagnostic, treatment and study of cardiovascular research. In particular, I will present EN-PESA, a Machine Learning algorithm ...

Dr. Fátima Sánchez Cabo graduated in Mathematics from the Complutense University of Madrid in 2000. From there she moved to the University of Manchester where she obtained a grant from the BBSRC to develop her doctoral work on statistical analysis and mathematical data modeling of microarrays. In 2005 she joined the Institute of Genomics and ...

Deploying large language models (LLMs) on edge devices has emerged as a compelling solution to achieve reduced costs, lower latency, enhanced privacy, and personalized user experiences. However, on-device deployment introduces unique challenges due to the resource constraints of edge devices, which differ significantly from high-throughput ...

Babak Ehteshami Bejnordi is a Research Scientist at Qualcomm AI Research in the Netherlands, leading a research group focusing on conditional computation for efficient deep learning. His primary research focus lies in the realm of efficient Deep Learning for Large Language Models (LLMs) and Computer Vision. His recent research works have been in ...

There is a desire for humans to ""understand"" decisions of machine learning (ML) models. Explainable AI (XAI) seemingly addresses this need by providing information beyond a model's output. XAI methods have been proposed to help identifying and correcting failure modes in models and data, to facilitate scientific discovery by identifying ...

Stefan Haufe is a joint Associate Professor of Uncertainty, Inverse Modeling, and Machine Learning at Technische Universität Berlin and Physikalisch-Technische Bundesanstalt Berlin. He also serves as a Group Leader at Charité - Universitätsmedizin Berlin, where his research focuses on developing advanced computational methods. His group ...