Popular GitHub Repositories for Non Iid

OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark

Open-source Visual programming for backend logic that integrates with existing codebases. Flyde bridges the gap between technical and non-technical team members. Product managers, designers, and backend developers can collaborate on the same visual flows.

FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai

Master Federated Learning in 2 Hours—Run It on Your PC!

Official Repository for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

An Open Source package that allows video game creators, AI researchers and hobbyists the opportunity to learn complex behaviors for their Non Player Characters or agents

GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

?? Transformer TTS: Implementation of a non-autoregressive Transformer based neural network for text to speech.

StreamSpeech is an “All in One” seamless model for offline and simultaneous speech recognition, speech translation and speech synthesis.

Streamlines and simplifies prompt design for both developers and non-technical users with a low code approach.

[ICASSP 2024] ? Matcha-TTS: A fast TTS architecture with conditional flow matching

A Non-Autoregressive Text-to-Speech (NAR-TTS) framework, including official PyTorch implementation of PortaSpeech (NeurIPS 2021) and DiffSpeech (AAAI 2022)

AI-Powered, Non-Intrusive Terminal Assistant

[CVPR2023] The official repo for OC-SORT: Observation-Centric SORT on video Multi-Object Tracking. OC-SORT is simple, online and robust to occlusion/non-linear motion.

Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

This project extends the idea of the innovative architecture of Kolmogorov-Arnold Networks (KAN) to the Convolutional Layers, changing the classic linear transformation of the convolution to learnable non linear activations in each pixel.

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

NISQA - Non-Intrusive Speech Quality and TTS Naturalness Assessment

OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

Unsupervised Feature Learning via Non-parametric Instance Discrimination