Stars
Curated list of the best truly open-source AI projects, models, tools, and infrastructure. Daily updated.
This is the official code for the paper Contrastive Hierarchical Clustering (ECML PKDD 2023)
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
PyTorch code for "Prototypical Contrastive Learning of Unsupervised Representations"
Code for paper: Are Large Language Models Post Hoc Explainers?
OpenXAI : Towards a Transparent Evaluation of Model Explanations
clustimage is a python package for unsupervised clustering of images.
Here we address the global structure preservation by tSNE and UMAP
Hybrid convolutional-recurrent neural networks for segmentation of birdsong and classification of elements
Open-source and modular toolbox for quantitative soundscape analysis in Python
PyTorch tutorial for using RNN and Encoder-Decoder RNN for time series forecasting
Applied Machine Learning Explainability Techniques, published by Packt
Implementation of the Johnson–Lindenstrauss transform in Python
Classifying audio using Wavelet transform and deep learning
Official code for NeurIPS 2022 paper https://arxiv.org/abs/2208.00780 Visual correspondence-based explanations improve AI robustness and human-AI team accuracy
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
Fast, flexible and easy to use probabilistic modelling in Python.
The collaborative word list
"DeepDPM: Deep Clustering With An Unknown Number of Clusters" [Ronen, Finder, and Freifeld, CVPR 2022]
Experiments with deep learning interpretability based on "Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning" (https://arxiv.org/abs/1803.04765)
Possiblistic Fuzzy C-Means Algorithm in Python
A machine learning toolkit for log-based anomaly detection [ISSRE'16]
Interpretable Machine Learning with Python, published by Packt