Christopher Walsh will review recent work on ‘somatic mutations’ — de novo mutations that are present in some brain cells but not in all cells of the body — in several neurological conditions associated with intellectual disability and seizures.
In this lecture, Thomas Schulthess will show how recent developments in architecture have moved us away from traditional abstractions, forcing software development and mathematical algorithms to acknowledge the physical reality of computing systems.
A canonical task in machine learning is to fit a model to a dataset. Sanjeev Arora will describe models fitted to real-life datasets, which display randomlike properties that can offer insights into the algorithms used for the task.
In this lecture, Eric Betzig will describe advanced optical tools being developed to help scientists delve deeper into the complexity of biological systems.