Flexible Feature visualization on PyTorch, for research and art 🔎 💻 🧠 🎨

Notebooks for learning about the layers of a convolutional neural network.

Filter visualization, Feature map visualization, Guided Backprop, GradCAM, Guided-GradCAM, Deep Dream

Visualization tool for point cloud and feature extracted from deep learning network

A TensorFlow implementation of Capsule Network as described in the paper Dynamic Routing Between Capsules

A tiny easily hackable implementation of a feature dashboard.

Custom Keras Callbacks for Feature Visualization, Class Activation Map, Grad-CAM

An interpretability library for pytorch

Official repository for the paper "How Well do Feature Visualizations Support Causal Understanding of CNN Activations?".

an implementation of Grad-CAM for tensorflowJS

This repository contains an end-to-end pipeline to train a convolutional neural network (CNN) for environmental sound classification on ESC-50. Serve the model for inference using Modal + a FastAPI endpoint. - Visualize model outputs (top predictions, input mel-spectrogram, waveform, and CNN feature maps).

object detection

Automatically generate a pdf report containing feature importance, baseline modelling, spurious correlation detection, and more, from a single command line input for any given ML CSV file

Like a CLIP + VQGAN. Except without a VQGAN.

The model classifies the advertisements by clicked or not-clicked and later identifies zero, low or high conversion rate.

[ICCV 2023] Code implementation for "Leaping Into Memories: Space-Time Deep Feature Synthesis"

Bilingual (Chinese/English) hands-on tutorial reproducing Olah et al. 2020 'Zoom In: An Introduction to Circuits' — mechanistic interpretability education

Visualizing Pneumonia Detection in Chest X-Ray Images: Enhancing Transparency and Understanding with Explainable AI using Grad-CAM and VGG19

OpenVision: A Fully-Open, Cost-Effective Family of Advanced Vision Encoders for Multimodal Learning. + A closer look in PyTorch!