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[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
Source code for lecture notes
Macros and functions to work with DSGE models.
Sophisticated space mission simulator. Calculate n-body trajectories, perform orbital maneuvers, apply various perturbations, plot variables, and more!
Mandelbrot fractal visualizer featuring perturbation based iteration methods, series approximation and multithreading.
GUI for rust-fractal-core, a mandelbrot fractal visualizer featuring perturbation based iteration methods, series approximation and multithreading.
Interpretable Explanations of Black Boxes by Meaningful Perturbation Pytorch
Replication code for simulating and estimation by GMM of DSGE models with higher-order statistics
Mandelbrot Generator based on perturbation and series approximation
perturbation of coupled model input over a space of input variables
Assessing consciousness by perturbing a dynamic mean-field whole-brain model fitted to empirical neuroimaging data
Perturbation toolbox to solve DSGE models with Matlab
Replication code for checking identification in nonlinear pruned DSGE models with Gaussian or Student's t distributed errors
A demonstration of perturbation of data
Implementation of two perturbation functions for Knapsack Problem
Second Year project (Module: Artificial Intelligence Methods), focusing on implementing and evaluating AI Optimisation methods.
Dataset of SOSAA model trajectory runs
Presentation given to Drexel XAI seminar on "Interpretable Explanations of Black Boxes by Meaningful Perturbation"