Delves into simulating network dynamics in in silico neuroscience, covering spontaneous and evoked activity, in-vitro and in-vivo simulations, and sensitivity analysis.
Introduces state-of-the-art methods in optimization and simulation, covering topics like statistical analysis, variance reduction, and simulation projects.
Explores training robots through reinforcement learning and learning from demonstration, highlighting challenges in human-robot interaction and data collection.
