AbCellera has an AI-driven antibody discovery platform, $650M liquidity, and an upcoming Phase 2 catalyst. Click here to read ...

Abstract: In several applications the information is naturally represented by graphs. Traditional approaches cope with graphical data structures using a preprocessing phase which transforms the graphs ...

AI is already writing most of its own code, and no regulatory framework can keep up with the changes it is implementing all ...

Retrieval-augmented generation (RAG) has emerged as a pivotal framework in AI, significantly enhancing the accuracy and relevance of responses generated by large language models (LLMs) leveraging ...

Abstract: Streaming graph signal (GS) estimation is common in various network systems. Several graph filter algorithms have been proposed for streaming GS estimation, but they still fail to reach ...

Welcome to Data Structures and Algorithms in Go! 🎉 This project is designed as a dynamic, hands-on resource for learning and practicing data structures and algorithms in the Go programming language.

This article introduces a model-based design, implementation, deployment, and execution methodology, with tools supporting the systematic composition of algorithms from generic and domain-specific ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Birgitta Böckeler, Distinguished Engineer at ...

While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...

Models that accurately predict properties based on chemical structure are valuable tools in the chemical sciences. However, for many properties, public and private training sets are typically small, ...

This paper introduces a novel application of spatial-temporal graph neural networks (ST-GNNs) to predict groundwater levels. Groundwater level prediction is inherently complex, influenced by various ...

The timely and accurate prediction of maize (Zea mays L.) yields prior to harvest is critical for food security and agricultural policy development. Currently, many researchers are using machine ...