Lecture
Discretisation of Continuous Time Systems
Related lectures (31)
Quantum Information
Explores the CHSH operator, self-testing, eigenstates, and quantifying randomness in quantum systems.
Efficient Stochastic Numerical Methods
Explores efficient stochastic numerical methods for modeling and learning, covering topics like the Analytical Engine and kinase inhibitors.
Boltzmann Machine
Introduces the Boltzmann Machine, covering expectation consistency, data clustering, and probability distribution functions.
Graph Coloring: Theory and Applications
Covers the theory and applications of graph coloring, focusing on disassortative stochastic block models and planted coloring.
Quantum Source Coding
Covers entropic notions in quantum sources, Shannon entropy, Von Neumann entropy, and source coding.
Digital Signal Processing: Theory
Covers the theory of digital signal processing, including sampling, transformation methods, digitization, and PID controllers.
Determinantal Point Processes and Extrapolation
Covers determinantal point processes, sine-process, and their extrapolation in different spaces.
Spatial Continuous Phenomena, SamplingMOOC: Introduction to Geographic Information Systems (part 2)
Explores sampling procedures for analyzing continuous geographical phenomena and their importance in reducing prediction uncertainty.
Generative Models: Self-Attention and Transformers
Covers generative models with a focus on self-attention and transformers, discussing sampling methods and empirical means.
Altitude Models: Derivative Variables
Covers global relief indicators, altitude models, slope, orientation, curvature, and morphological indices for terrain description.