GitHub

Python implementation of the TurboQuant and QJL vector quantization algorithms.

turboquant-py implements the TurboQuant and QJL vector quantization algorithms from Google Research (ICLR 2026 / AISTATS 2026). It compresses high-dimensional floating-point vectors to 1-4 bits per ...
IEEE

SQUAT: Stateful Quantization-Aware Training in Recurrent Spiking Neural Networks

Abstract: Weight quantization is used to deploy high-performance deep learning models on resource-limited hardware, enabling the use of low-precision integers for storage and computation. Spiking ...
GitHub

Locally Optimized Product Quantization

This is Python training and testing code for Locally Optimized Product Quantization (LOPQ) models, as well as Spark scripts to scale training to hundreds of millions of vectors. The resulting model ...
来自MSN

MI Physics Lecture Chapter 8; Energy Quantization

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...
theregister

Honey, I shrunk the LLM! A beginner's guide to quantization – and testing it

HANDS ON If you hop on Hugging Face and start browsing through large language models, you'll quickly notice a trend: Most have been trained at 16-bit floating point of Brain-float precision. FP16 and ...