Lectures related to Blue | EPFL Graph Search

Covers the basics of reinforcement learning, including trial-and-error learning, Q-learning, deep RL, and applications in gaming and planning.

Covers estimation of unknown parameters, analyzing model fit, bird prey response, and model diagnostics.

Delves into Chaos Theory, exploring chaotic systems, sensitivity to initial conditions, and the dynamics of the double pendulum.

Covers the distribution of data in the FlowField class, focusing on gridpoint calculations and MPI usage.

Explores spectral sensitization in photography, panchromatic films, color vision, and reproduction methods.

Covers replication, strong consistency, failure modes, network models, and the Paxos algorithm.

Covers basic probability theory, ANOVA, experimental design, and statistical reporting errors.