ZipNN: a new lossless compression method adapted to neural networks
The rapid advancement of large language models (LLMs) has exposed critical infrastructure challenges in model implementation and communication. As models ...
Tag: networks
This Amazon AI paper introduces DF-GNN: a dynamic kernel fusion framework for accelerating attention graph neural networks on GPUs
Graph neural networks (GNN) is a rapidly advancing field in machine learning, specifically designed to analyze graphically structured data representing ...
NFT sales fall to $146.5 million: Ethereum and Bitcoin networks recover
As bitcoin continues to face resistance near the $100,000 mark, the nft market has seen a 1.6% drop, with total ...
GRAF: A machine learning framework that converts multiplexed heterogeneous networks into homogeneous networks to make them more suitable for graph representation learning
Real-world networks, such as those in biomedical and multi-omics datasets, often exhibit complex structures characterized by multiple types of nodes ...
Building Efficient Neural Networks with JAX
Flax is an advanced neural network library built on top of JAX, aimed at giving researchers and developers a flexible, ...
Stock Drivers: Airbnb, Sweetgreen, Arista Networks and More
stocks rose midday Friday, with major benchmark indices hitting all-time highs. The S&P 500 rose 0.6%, while the tech-heavy Nasdaq ...
Total value locked reaches $5.7 billion, ranking third among networks
This article is also available in Spanish. A recent report from crypto data and research firm Messari shed light on ...
The Verge's favorite social networks
Social media has become more disconnected, to say the least. Two years ago, Elon Musk began transforming twitter into what ...
XElemNet: A Machine Learning Framework Applying Explainable AI (XAI) Suite for Deep Neural Networks in Materials Science
Deep learning has made progress in several fields and has also made its way into materials sciences. From tasks like ...
Improving task scheduling in linguistic agents: Leveraging graph neural networks to improve task decomposition and decision making in large language models
Task planning in linguistic agents is gaining attention in LLM research, focusing on breaking down complex tasks into manageable subtasks ...
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