Source code for lecture notes

Second Year project (Module: Artificial Intelligence Methods), focusing on implementing and evaluating AI Optimisation methods.

A demonstration of perturbation of data

Implementation of two perturbation functions for Knapsack Problem

ICASSP 2021 accepted paper

Presentation given to Drexel XAI seminar on "Interpretable Explanations of Black Boxes by Meaningful Perturbation"

Perturbation toolbox to solve DSGE models with Matlab

Replication code for simulating and estimation by GMM of DSGE models with higher-order statistics

Replication code for checking identification in nonlinear pruned DSGE models with Gaussian or Student's t distributed errors

Assessing consciousness by perturbing a dynamic mean-field whole-brain model fitted to empirical neuroimaging data

GUI for rust-fractal-core, a mandelbrot fractal visualizer featuring perturbation based iteration methods, series approximation and multithreading.

Mandelbrot fractal visualizer featuring perturbation based iteration methods, series approximation and multithreading.

Dataset of SOSAA model trajectory runs

[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

Python implementation of a data perturbation method to determine relevant features for NN learning

Interpretable Explanations of Black Boxes by Meaningful Perturbation Pytorch

Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.

Exploring perturbation stategies to improve LIME explanations stability.

scPerturb: A resource and a python/R tool for single-cell perturbation data

Sophisticated astrodynamics and space mission simulator. Calculate n-body trajectories, perform orbital maneuvers, apply various perturbations, generate plots, and more! Minimal dependencies.