In mathematics and digital signal processing, quantization is the process of mapping input values from a large set (often a continuous set) to output values in a (countable) smaller set, often …

Nov 6, 2025 · Quantization is a model optimization technique that reduces the precision of numerical values such as weights and activations in models to make them faster and more …

Quantization is the process of mapping continuous infinite values to a smaller set of discrete finite values. In the context of simulation and embedded computing, it is about approximating real …

Jul 22, 2024 · In this post, I will introduce the field of quantization in the context of language modeling and explore concepts one by one to develop an intuition about the field. We will …

Nov 24, 2025 · Quantization has emerged as a crucial technique to address this challenge, enabling resource-intensive models to run on constrained hardware. The NVIDIA TensorRT …

What is quantization in machine learning? Quantization is a technique for lightening the load of executing machine learning and artificial intelligence (AI) models. It aims to reduce the …

Jul 20, 2025 · Among many optimization techniques to improve AI inference performance, quantization has become an essential method when deploying modern AI models into real …

Quantization is representing the sampled values of the amplitude by a finite set of levels, which means converting a continuous-amplitude sample into a discrete-time signal.

What is a Quantization? Quantization is the process of converting continuous data to discrete values. It's used in various fields like signal processing and machine learning to reduce data size.

Jun 11, 2025 · Quantization is a fundamental process in signal processing that involves the conversion of a continuous signal into a discrete signal. This process is crucial in various …