patrick-knab's Stars
Significant-Gravitas/AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
facebookresearch/segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
marcotcr/lime
Lime: Explaining the predictions of any machine learning classifier
interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.
ashishpatel26/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network
Tools to Design or Visualize Architecture of Neural Network
keplr-io/quiver
Interactive convnet features visualization for Keras
jacobgil/keras-grad-cam
An implementation of Grad-CAM with keras
JEddy92/TimeSeries_Seq2Seq
This repo aims to be a useful collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.
sebastian-lapuschkin/lrp_toolbox
The LRP Toolbox provides simple and accessible stand-alone implementations of LRP for artificial neural networks supporting Matlab and Python. The Toolbox realizes LRP functionality for the Caffe Deep Learning Framework as an extension of Caffe source code published in 10/2015.
moboehle/Pytorch-LRP
Basic LRP implementation in PyTorch
aliasgharkhani/SLiMe
1-shot image segmentation using Stable Diffusion
atulshanbhag/Layerwise-Relevance-Propagation
Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers
emanuel-metzenthin/Lime-For-Time
Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification
kingridda/voice-cloning-AI
Voice cloning AI (deepfake for voice). Using cloned voice from only 5-10 seconds of targeted voice.
x-y-zhao/BayLime
bayesian lime
ZhengzeZhou/slime
thutzr/GLIME-General-Stable-and-Local-LIME-Explanation
GLIME is a post-hoc explanation method which is proved to be much more stable and faithful than LIME.