What do deep neural networks "forget"?

Robust Mini-batch Gradient Descent models

This repository includes the R code used for the project "Investigating robust partitional clustering methods", written by Efthymios Costa. The project is supervised by Dr. Ioanna Papatsouma (Imperial College London) and co-supervised by Professor Alastair Young (Imperial College London).

Paper Summary for Relations between Trustworthy AI Concepts

Simple math project about how designing robust and reliable paper helicopters.

Main project for the Real-time programming course at NTNU. Coordinating N different elevators in a building, in order to efficiently deal with requests handling the robustness of the system.

Analysis of robust classification algorithms for overcoming class-dependant labelling noise: Forward, Importance Reweighting and T-revision. We demonstrate methods for estimating the transition matrix in order to obtain better classifier performance when working with noisy data.

A web app to record daily sales information of your bussiness.

Evaluate robustness of image processing algorithms

A master thesis report "Optimizing Web Extraction Queries For Robustness"

Finding label errors in datasets and learning with noisy labels.

Robust Effective and Resource Efficient Deep Neural networks

Matlab scripts for implementing different stochastic methods

Digital immortalisation of many hours of my life solving regular bioinformatic problems.

Computing the Structured Singular Value of a matrix.

Source code/webpage/demos for the What-If Tool

CUDA implementation of the best model in the Robust Mini-batch Gradient Descent repo

This project Implements the paper “Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces” using the Python language.

Calculation of sensitivity coefficients and visualization

A design system 😋 that has an opinionated API ❤️, modular and accessible cool ui components for faster development 🥂.