we use activation maximization and GANs to discover patterns that contributes to the concept of naturalness in satellite imagery
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Updated
May 7, 2024 - Python
we use activation maximization and GANs to discover patterns that contributes to the concept of naturalness in satellite imagery
🥭 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
An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization
Neural network visualization toolkit for tf.keras
The official repo for GECCO 2022 paper High-Performance Evolutionary Algorithms for Online Neuronal Control in vivo and in silico
Exploration of various methods to visualize layers of deep Convolutional Neural Networks using Pytorch.
Sampling from π_n(S^2). Application of optimization and machine learning methods to problems of algebraic topology
Explainability of Brain Tumour Segmentation Models
Explainability of Deep Learning Models
Pytorch implementation of various neural network interpretability methods
A set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch based deep neural networks.
This repository is to introduce the application of Activation Maximization for audio-domain data.
Class Activation Map (CAM)
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