A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...
Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...
Smaller models, lightweight frameworks, specialized hardware, and other innovations are bringing AI out of the cloud and into clients, servers, and devices on the edge of the network.
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
On Tuesday afternoon, Bob Starkey was in the LSU women’s basketball team’s locker room when he decided to take out his phone and snap a photo he’d later post to Instagram. Starkey wanted people to see ...
Abstract: Vector-Quantization (VQ) based discrete generative models are widely used to learn powerful high-quality (HQ) priors for blind image restoration (BIR). In this paper, we diagnose the ...
An unofficial PyTorch implementation of "Autoregressive Speech Synthesis without Vector Quantization" paper. This repository provides a complete pipeline for training and inference of the MELLE model.
Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
Abstract: Vector quantization-based image semantic communication systems have successfully boosted transmission efficiency. However, existing models like Vector Quantized Variational Autoencoder 2 ...
VQ-VLA is an innovative vector quantization based action tokenizer built upon the largest-scale action trajectory dataset to date, leveraging over 100 times more data than previous approaches. It ...
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