A demonstration of perturbation of data

Implementation of two perturbation functions for Knapsack Problem

ICASSP 2021 accepted paper

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

Interpretable Explanations of Black Boxes by Meaningful Perturbation Pytorch

Exploring perturbation stategies to improve LIME explanations stability.

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

Symbolic Perturbation Theory (SymPT) is a Python package for symbolic perturbative transformations on quantum systems. SymPT helps compute effective Hamiltonians for both time-independent and time-dependent systems at both operator and matrix level.

M0dular Action System & Interface, Custom AI/AGENT Framework (made by a non-coder)

MSAffect is a computational pipeline to evaluate the robustness of AlphaFold2 protein structure predictions under adversarial MSA perturbations to identify structural sensitivity and confidence shifts in neural-network-based folding.

Single-cell Analysis of Perturbational Effects using Machine Learning

perturbation of coupled model input over a space of input variables

A Python simulator for modeling gene expression perturbations using a recursive, depth-limited path summation model.

Single-cell perturbation analysis