Nature

Stochastic modelling articles from across Nature Portfolio

Stochastic modelling is the development of mathematical models for non-deterministic physical systems, which can adopt many possible behaviours starting from any given initial condition. Monte-Carlo ...
IEEE

Autoencoder-Augmented Graph Neural Networks for Accurate and Scalable Structure Recognition in Analog/Mixed-Signal Schematics

Abstract: The increasing complexity of Analog/Mixed-Signal (AMS) schematics has been posing significant challenges in structure recognition, particularly in the intellectual property (IP) industry, ...
IEEE

Modified Overcomplete Autoencoder for Anomaly Detection Based on TinyML

Abstract: This letter explores the architecture of tiny machine learning (TinyML). Deploying machine learning into embedded devices is challenging due to the limited computation power and memory space ...
GitHub

SVG: Latent Diffusion Model without Variational Autoencoder

SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.
GitHub

Awesome Learning-Based Controls

Learning-Based Controls is an emerging field at the intersection of Control Theory for Dynamic Systems and Machine Learning, particularly Deep Learning and Reinforcement Learning. This repository ...