Mahyar Fazlyab: Control‐Theoretic Tools in Analysis and Synthesis of Neural Network Driven Systems

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Mahyar Fazlyab presents \

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Compositional Curvature Bounds for Deep Neural Networks

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Learning Performance-oriented CBFs Under Complex Safety Constraints and Limited Actuation

(1:21)

An Introduction to Neural Network Analysis via Semidefinite Programming

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Spotlight Talks - Various

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A BnB method for reachability analysis of neural autonomous systems using Lipschitz bounds

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Gradient-Regularized Out-of-Distribution Detection

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Optimization-in-the-loop ML for Energy and Climate | Priya Donti | Smart Grid Seminar

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How to Build \u0026 Backtest Bull Call Spread Trading Algorithm with Python

(20:21)

Introduction to Microgrids | Learn to use

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Stephen Boyd: Embedded Convex Optimization for Control

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Kuramoto talks about the Kuramoto model

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Lecture 20: Neural Network based control for Robot Manipulator

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Mark Cannon - Adaptive Model Predictive Control: Robustness, Performance Enhancement \u0026 Param. Estim.

(55:11)

MAE5790-25 Using chaos to send secret messages

(1:5:22)

Model Predictive Control: The Impact of Computation on Control: The 4th Wook Hyun Kwon Lecture

(1:47:8)

2011 Simons Lectures - Steven Strogatz, Coupled Oscillators That Synchronize Themselves

(58:9)

DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting | RTCL.TV

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[CDC 2021] Tutorial: Neural Network Verification in Control

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PINN-CBF: Safety Filtering for Obstacle Avoidance

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Impulsive Synchronization and Desynchronization of Integrate and Fire Oscillators

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Manfred Morari (University of Pennsylvania): \

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Closing the Loop: Dynamic State Estimation and Feedback Optimization of Distribution Grids

(17:47)

Incorporating Constraints into Deep Learning, with Application to Grid Optimization

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Optimal design and critical analysis of a high resolution video plenoptic demonstrator

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