perturbation-analysis

There are 0 repository under perturbation-analysis topic.

mjg211 / phaseR
Development version of phaseR, an R package for phase plane analysis of one- and two-dimensional autonomous ODE systems
biological-modeling differential-equations dynamical-systems ecological-modelling lotka-volterra manifolds modeling-dynamic-systems morris-lecar perturbation-analysis phase-plane sir-model species-interactions van-der-pol
Language:R 15
DelSquared / Brownian-Motion
Python solver for the Brownian, Stochastic, or Noisy Differential Equations
langevin-dynamics langevin-equations langevin-diffusion langevin stochastic-processes stochastic-differential-equations noise-maps noisy-differential-equations oscillator brownian-motion brownian-dynamics ode-solver ode-solver-stochastic euler-method midpoint-method runge-kutta-methods random-walk non-equilibrium noisy-systems perturbation-analysis
Language:Python 14
roberto1648 / adversarial-perturbations-on-images-and-videos
Code and data from the paper "Targeted Nonlinear Adversarial Perturbations in Images and Videos".
adversarial-examples adversarial-learning adversarial-networks explainable-artificial-intelligence perturbation-analysis
Language:Jupyter Notebook 10
epigen / mixscape_seurat
A Snakemake workflow for performing perturbation analyses of pooled (multimodal) CRISPR screens with sc/snRNA-seq read-out (scCRISPR-seq) powered by the R package Seurat's method Mixscape.
bioinformatics biomedical-data-science perturbation-analysis sccrispr-seq scrna-seq single-cell snakemake snrna-seq visualization workflow
Language:R 7
swamiviv / guided_perturbations
Guided Perturbations: Self-Corrective Behavior in Convolutional Neural Networks
adversarial-machine-learning semantic-segmentation uncertainty-neural-networks perturbation-analysis deep-learning cnn
Language:Python 3
auroramaurizio / GRAPE
GRAph Parallel Environment
failure-analysis graph-theory-algorithms hpc perturbation-analysis python-package reconfiguration risk-management safety-monitoring screening ships toplogy damage-propagation interconnected-systems
Language:Python 1
auroramaurizio / PEAR
PEAR is a Python program that takes advantage of Petri nets and logical conditions to develop a screening tool aimed at studying the effect of perturbations in interconnected systems.
damage-propagation interconnection perturbation-analysis petri-nets python-package safety-monitoring screening
Language:Python 0
cristopherarenas / cc5_perturbation_analysis
Perturbation Analysis for Parabolic Partial Differential Equations
partial-differential-equations perturbation-analysis multiscale-simulation finite-difference fast-fourier-transform numerical-methods
Language:Jupyter Notebook 0
emilbiju / MaxScatterTSP
Perturbation Analysis of Practical Algorithms for the Maximum Scatter Travelling Salesman Problem @ ALENEX '22
approximation-algorithms travelling-salesman-problem perturbation-analysis
Language:C++