Class Activation Map (CAM)
-
Updated
Nov 26, 2020 - Jupyter Notebook
Class Activation Map (CAM)
This repository is to introduce the application of Activation Maximization for audio-domain data.
🥭 MANGO: Maximization of neural Activation via Non-Gradient Optimization
we use activation maximization and GANs to discover patterns that contributes to the concept of naturalness in satellite imagery
Sampling from π_n(S^2). Application of optimization and machine learning methods to problems of algebraic topology
Exploration of various methods to visualize layers of deep Convolutional Neural Networks using Pytorch.
Official code repo for the BigGAN paper of the PonceLab. Neural Guided Image Synthesis in multiple Generator spaces
Explainability of Brain Tumour Segmentation Models
The official repo for GECCO 2022 paper High-Performance Evolutionary Algorithms for Online Neuronal Control in vivo and in silico
Explainability of Deep Learning Models
A set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch based deep neural networks.
An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization
Pytorch implementation of various neural network interpretability methods
Neural network visualization toolkit for tf.keras
Add a description, image, and links to the activation-maximization topic page so that developers can more easily learn about it.
To associate your repository with the activation-maximization topic, visit your repo's landing page and select "manage topics."