Hub

Browse all posts in the Hub category.

1 to 6 of 19

14JUL 2026
Akademy
From Optimal Control to Reinforcement Learning: A Motivating Example from the Perspective of Linear Quadratic Regulators
From Optimal Control to Reinforcement Learning: A Motivating Example from the Perspective of Linear Quadratic Regulators Fredson Silva De Souza Aguiar, Visiting Master Student. University of Sorbonne Paris Nord Repository with code and trained models available at FAU DCN-AvH GitHub: https://github.com/DCN-FAU-AvH/oc_rl_lqr We motivate the study of interconnections and relevant results at the interface between Control […]From Optimal Control to Reinforcement Learning: A Motivating Example from the Perspective of Linear Quadratic Regulators Fredson Silva De Souza Aguiar, Visiting Master Student. University of Sorbonne Paris Nord Repository with code and trained models available at FAU DCN-AvH GitHub: https://github.com/DCN-FAU-AvH/oc_rl_lqr We motivate the study of interconnections and relevant results at the interface between Control […]
Read more about From Optimal Control to Reinforcement Learning: A Motivating Example from the Perspective of Linear Quadratic Regulators
14NOV 2025
Hub
Sentiment Analysis with Transformers
Sentiment Analysis with Transformers This post includes an app SentimentAnalysisTransformersApp created for a public outreach activity organized by the Chair for Dynamics, Control, Machine Learning and Numerics – Alexander von Humboldt Professorship (FAU DCN-AvH) during the Lange Nacht der Wissenschaften 2025 (Long Night Sciences 2025). Live demo https://albertalcalde.github.io/SentimentAnalysisTransformersApp/ Overview This interactive app lets you type […]Sentiment Analysis with Transformers This post includes an app SentimentAnalysisTransformersApp created for a public outreach activity organized by the Chair for Dynamics, Control, Machine Learning and Numerics – Alexander von Humboldt Professorship (FAU DCN-AvH) during the Lange Nacht der Wissenschaften 2025 (Long Night Sciences 2025). Live demo https://albertalcalde.github.io/SentimentAnalysisTransformersApp/ Overview This interactive app lets you type […]
Read more about Sentiment Analysis with Transformers
03JUL 2024
Hub
Clustering in pure-attention hardmax transformers and its role in sentiment analysis
Clustering in pure-attention hardmax transformers and its role in sentiment analysis This post provides an overview of the results in the paper Clustering in Pure-Attention Hardmax Transformers and its Role in Sentiment Analysis by Albert Alcalde, Giovanni Fantuzzi, and Enrique Zuazua [1]. Codes used to reproduce the simulations can be found at the repository: https://github.com/DCN-FAU-AvH/clustering-hardmax-transformers […]Clustering in pure-attention hardmax transformers and its role in sentiment analysis This post provides an overview of the results in the paper Clustering in Pure-Attention Hardmax Transformers and its Role in Sentiment Analysis by Albert Alcalde, Giovanni Fantuzzi, and Enrique Zuazua [1]. Codes used to reproduce the simulations can be found at the repository: https://github.com/DCN-FAU-AvH/clustering-hardmax-transformers […]
Read more about Clustering in pure-attention hardmax transformers and its role in sentiment analysis
01DEC 2023
Hub
PINNs Introductory Code for the Heat Equation
PINNs Introductory Code for the Heat Equation This repository provides some basic insights on Physics Informed Neural Networks (PINNs) and their implementation. PINNs are numerical methods based on the universal approximation capacity of neural networks, aiming to approximate solutions of partial differential equations. Recently, extensive focus has been on approximating solutions of various equations, leading […]PINNs Introductory Code for the Heat Equation This repository provides some basic insights on Physics Informed Neural Networks (PINNs) and their implementation. PINNs are numerical methods based on the universal approximation capacity of neural networks, aiming to approximate solutions of partial differential equations. Recently, extensive focus has been on approximating solutions of various equations, leading […]
Read more about PINNs Introductory Code for the Heat Equation
04AUG 2023
Hub
Combined convection and diffusion in a network. A numerical analysis
Combined convection and diffusion in a network. A numerical analysis. The problem: a contaminant in a network of water pipes Imagine that there is a network of pipes full of water. The water is flowing from some source nodes (say, some water plants) to some destination nodes (say, people’s homes). A contaminant is present in […]
Read more about Combined convection and diffusion in a network. A numerical analysis
12JUL 2023
Hub
The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach
The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach Motivation This post shows the source code from the paper “The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach”. (See reference below) We study the combination of the alternating direction method of multipliers (ADMM) with physics-informed neural networks (PINNs) for […]The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach Motivation This post shows the source code from the paper “The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach”. (See reference below) We study the combination of the alternating direction method of multipliers (ADMM) with physics-informed neural networks (PINNs) for […]
Read more about The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach