Explores advancements in robot learning for autonomy at scale, covering deep learning challenges, efficient architecture, benchmarking results, and societal implications.
Covers the principles of Scanning Electron Microscopy, including SEM signals, detectors, and energy spectrum of electrons, as well as the efficiency of X-ray generation.
Explores bug-finding, verification, and the use of learning-aided approaches in program reasoning, showcasing examples like the Heartbleed bug and differential Bayesian reasoning.
