A new technical paper titled “A Case for Hypergraphs to Model and Map SNNs on Neuromorphic Hardware” was published by researchers at Politecnico di Milano. “Executing Spiking Neural Networks (SNNs) on ...
A standalone cubical type theory kernel, about 17K lines of Go. Small enough to read, complete enough to use. Univalence computes. HITs reduce. Compiles to a single binary with no runtime dependencies ...
Background: Molecular interactions are central to numerous challenges in chemistry and the life sciences. Whether in solute–solvent dissolution, adverse drug–drug interactions, or protein complex ...
Large Language Models (LLMs) have set new benchmarks in natural language processing, but their tendency for hallucination—generating inaccurate outputs—remains a critical issue for knowledge-intensive ...
Abstract: Hypergraph community detection reveals both mesoscale structures and functional characteristics of real-life hypergraphs. Although many methods have been developed from diverse perspectives, ...
An illustration representing a hypergraph in which people within a large organization are connected by multi-way relationships. A hypergraph can model the complexity of these connections. Picture a ...
Scientists usually use a hypergraph model to predict dynamic behaviors. But the opposite problem is interesting, too. What if researchers can observe the dynamics but don't have access to a reliable ...
In a network, pairs of individual elements, or nodes, connect to each other; those connections can represent a sprawling system with myriad individual links. A hypergraph goes deeper: It gives ...
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