Neural network visualization toolkit for tf.keras
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Updated
Mar 25, 2024 - Python
Neural network visualization toolkit for tf.keras
Pytorch implementation of various neural network interpretability methods
An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization
A set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch based deep neural networks.
Explainability of Deep Learning Models
Exploration of various methods to visualize layers of deep Convolutional Neural Networks using Pytorch.
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
Sampling from π_n(S^2). Application of optimization and machine learning methods to problems of algebraic topology
🥭 MANGO: Maximization of neural Activation via Non-Gradient Optimization
Official code repo for the BigGAN paper of the PonceLab. Neural Guided Image Synthesis in multiple Generator spaces
we use activation maximization and GANs to discover patterns that contributes to the concept of naturalness in satellite imagery
Class Activation Map (CAM)
This repository is to introduce the application of Activation Maximization for audio-domain data.
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