Nature

Vector Quantization and Learning Algorithms

Vector quantisation and its associated learning algorithms form an essential framework within modern machine learning, providing interpretable and computationally efficient methods for data ...
IEEE

VQ-LLM: High-performance Code Generation for Vector Quantization Augmented LLM Inference

Abstract: Vector quantization (VQ), which treats a vector as a compression unit, gains increasing research interests for its potential to accelerate large language models (LLMs). Compared to ...
IEEE

Lattice Vector Quantization For Normal Mesh Geometry Coding

Abstract: Multiresolution representation of surface meshes is known to be a powerful tool for modeling complex 3D objects. Among the existing schemes, normal meshes have proven to be very attractive ...
GitHub

dy2009/vector-quantize-pytorch_for_SoundStream

A vector quantization library originally transcribed from Deepmind's tensorflow implementation, made conveniently into a package. It uses exponential moving averages to update the dictionary. VQ has ...
GitHub

UniVQ: Unified Time Series Forecasting with Vector Quantization

Time series forecasting faces significant challenges due to highly heterogeneous distributions across domains and limited data coverage of real-world scenarios. UniVQ addresses these challenges ...
blockchain

Multi-vector Image Retrieval AI Course: Outperforming Single-vector Methods with ColBERT, ColPali, and MUVERA

According to DeepLearning.AI on Twitter, a new short course in collaboration with Qdrant introduces AI professionals to advanced multi-vector image retrieval techniques. Led by Senior Developer ...
Business Wire

Elastic Announces Faster Filtered Vector Search with ACORN-1 and Default Better Binary Quantization Compression

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, announced new performance and cost-efficiency breakthroughs with two significant enhancements to its vector search. Users ...