Discrete-Time Dynamical Systems

This video shows how discrete-time dynamical systems may be induced from continuous-time systems.

Singular Value Decomposition (SVD): Matrix Approximation

This video describes how the singular value decomposition (SVD) can be used for matrix approximation.

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 3 - Model-Fr...

Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group

RL Course by David Silver - Lecture 4: Model-Free Prediction

An introduction to Monte-Carlo Learning and Temporal Difference Learning

Using a Homogeneous Transformation Matrix to Combine Rotation and Translatio...

In this video we discuss how to properly deal with coordinate frames that are both rotated and translated from one another. We develop a homogeneous transformation matrix which combines a...

Coriolis Effect Demonstration (with Drones)

We demonstrate how rotating reference frames give rise to the Coriolis effect and centrifugal acceleration. In this video, we approach this as a simple physics demonstration and examine...

Data-Driven Control: Balancing Transformation

In this lecture, we derive the balancing coordinate transformation that makes the controllability and observability Gramians equal and diagonal. This is the critical step in balanced model...

Parseval's Theorem

Parseval's theorem is an important result in Fourier analysis that can be used to put guarantees on the accuracy of signal approximation in the Fourier domain.

Identifying Dominant Balance Physics from Data - Jared Callaham

This video illustrates a new algorithm to identify local dominant physical balance relations from multiscale spatiotemporal data.

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 13 - Fast Rei...

Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group

RL Course by David Silver - Lecture 9: Exploration and Exploitation

An overview of multi-armed bandits, contextual bandits and Markov Decision Processes.

Simple Vector Mechanics: Inner Product, Scalar/Vector Projection, and Cross ...

In this video we discuss several simple vector operations such as: 1. Computing the magnitude of a vector 2. The inner/dot product 3. The scalar and vector projection 4. The cross product

Data-Driven Control: Eigensystem Realization Algorithm Procedure

In this lecture, we describe the eigensystem realization algorithm (ERA) in detail, including step-by-step algorithmic instructions.

Koopman Spectral Analysis (Representations)

In this video, we explore how to obtain finite-dimensional representations of the Koopman operator from data, using regression.

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 7 - Imitation...

Professor Emma Brunskill

Assistant Professor, Computer Science

Stanford AI for Human Impact Lab

Stanford Artificial Intelligence Lab

Statistical Machine Learning Group

Trimming a Model of a Dynamic System Using Numerical Optimization

In this video we show how to find a trim point of a dynamic system using numerical optimization techniques. We generate a cost function that corresponds to a straight and level flight...

Singular Value Decomposition (SVD): Mathematical Overview

This video presents a mathematical overview of the singular value decomposition (SVD).

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 5 - Value Fun...

Professor Emma Brunskill

Assistant Professor, Computer Science

Stanford AI for Human Impact Lab

Stanford Artificial Intelligence Lab

Statistical Machine Learning Group

RL Course by David Silver - Lecture 3: Planning by Dynamic Programming

Introduces policy evaluation and iteration, value iteration, extensions to dynamic programming and contraction mapping.