Popular GitHub Repositories for Variance Reduction

Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, RTX Video Super Resolution VSR, SRMD, RealSR, Anime4K, RIFE, IFRNet, CAIN, DAIN, and ACNet.

Uniform Manifold Approximation and Projection

SwinIR: Image Restoration Using Swin Transformer (official repository)

Recurrent neural network for audio noise reduction

Module for automatic summarization of text documents and HTML pages.

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

QualityScaler - image/video AI upscaler app

Collection of popular and reproducible image denoising works.

Text Classification Algorithms: A Survey

AIOps学习资料汇总，欢迎一起补全这个仓库，欢迎star

:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps

ARCH models in Python

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

[ECCV] Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration. Advances in Image Manipulation (AIM) workshop ECCV 2022. Try it out! over 3.3M runs https://replicate.com/mv-lab/swin2sr

Tensorflow 2.x implementation of the DTLN real time speech denoising model. With TF-lite, ONNX and real-time audio processing support.

PyTorch implementation of "FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."

Minimum-distortion embedding with PyTorch

[EMNLP 2024 Industry Track] This is the official PyTorch implementation of "LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit".

Machine Learning notebooks for refreshing concepts.