Abstract: Graph convolutional networks (GCNs) are a widely used method for graph representation learning. To elucidate their capabilities and limitations for graph classification, we investigate their ...

A new framework called SkillWeaver tackles AI agent tool routing by skipping full-library loading, cutting token use 99% on ...

It isn't approved by the FDA, but we found an experimental weight-loss drug called retatrutide for sale at a local ...

The Graph offers access to competitive and cost-efficient decentralized data sets. The network boasts a 99.99% uptime and 24/7 availability. Central to The Graph’s operations are subgraphs, APIs that ...

Abstract: Fine-grained Zero-shot Learning on the large-scale dataset ImageNet21K is an important task that has promising perspectives in many real-world scenarios. One typical solution is to ...

The speakers discuss Netflix’s architecture for surviving extreme traffic spikes. They explain the mechanics of prioritized load shedding embedded in their Envoy sidecar proxy, allowing user-initiated ...

Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...

LLVM powers the core development tools, operating systems, and most applications at Apple Computer, where it long ago ...

Results of investigations into limiting factors of photosynthesis can be presented as a graph. Typically, these will have the following profiles. The rate of photosynthesis will increase as light ...

Implementation of Neural Scene Graphs, that optimizes multiple radiance fields to represent different objects and a static scene background. Learned representations can be rendered with novel object ...

The release includes an embedded MCP server that exposes Spring project analytics to AI coding assistants, along with first-class support for Spring AI and automated property refactoring.