Popular GitHub Repositories for Post Hoc Explanation

A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Recognition, Voice Activity Detection, Text Post-processing etc.

Curated list of datasets and tools for post-training.

A curated list of the latest breakthroughs in AI (in 2022) by release date with a clear video explanation, link to a more in-depth article, and code.

A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.

A library for debugging/inspecting machine learning classifiers and explaining their predictions

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and?code

Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Ranking (CTR/CVR prediction), Post Ranking, Large Model (Generative Recommendation, LLM), Transfer learning, Reinforcement Learning and so on.

Awesome Reasoning LLM Tutorial/Survey/Guide

Synthetic data curation for post-training and structured data extraction

Code that accompanies my blog post outlining five video classification methods in Keras and TensorFlow

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.

[ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization

365 Days Computer Vision Learning Linkedin Post

Code accompanying my blog post: So, what is a physics-informed neural network?

Cross-platform SDK for facial motion capture producing blendshapes and rigid head poses in 3D space in realtime from photos or videos.

Explore the Multimodal “Aha Moment” on 2B Model

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

code for our NAACL 2019 paper: "BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis"

Source code for my blog post "Getting started with TensorFlow on iOS"