Publication

Recurrent Neural Network based MPC for Process Industries

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Recurrent Neural Network based MPC for Process Industries

Graph Chatbot

Chattez avec Graph Search

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

Data-driven LPV Control for Micro-disturbance Rejection in a Hybrid Isolation Platform

Koopman-based Data-driven Robust Control of Nonlinear Systems Using Integral Quadratic Constraints

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Incorporating Projective Geometry into Deep Learning

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Incorporating Projective Geometry into Deep Learning

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Data-driven LPV Control for Micro-disturbance Rejection in a Hybrid Isolation Platform

Koopman-based Data-driven Robust Control of Nonlinear Systems Using Integral Quadratic Constraints

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination