Jakob Robnik

David Rügamer, LMU professor working on uncertainty in deep models; Emanuel Sommer, PhD researcher building practical JAX sampling tools; Jakob Robnik, Berkeley physicist developing the Microcanonical Langevin sampler. They discuss scaling Bayesian neural networks, fast sampling tricks and software, microcanonical dynamics, bottlenecks in high dimensions, hybrid warm-start strategies, and tooling for practical uncertainty quantification.