Aggregate to Adapt: Node-Centric Aggregation for Multi-Source-Free Graph Domain Adaptation (WWW-2025). This is a PyTorch implementation of the GraphATA algorithm, which tries to address the ...

Probing the Influence of the Protein Scaffold on H-Cluster Reactivity via Gain-of-Function Studies─Improved H 2 Evolution and O 2 Tolerance through Rational Design of [FeFe] Hydrogenase ...

The fast-rising pace of attacks is driving a graph database arms race across leading cybersecurity providers.

First, I want to express my sincere gratitude for your contribution of CardBench to the field of Cardinality Estimation—it has been incredibly helpful in my work. I'm replicating the Instance based ...

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The linear framework allows the steady-state probabilities of graph vertices to be calculated as rational algebraic functions of the labels (Eq. 4). Importantly, this can be done whether or not the ...

Manifold learning, rooted in the manifold assumption, reveals low-dimensional structures within input data, positing that the data exists on a low-dimensional manifold within a high-dimensional ...

Download this Trigonometric Sin Cos Tan Function Graph Diagram Goniometric Mathematical Function Sine Cosine Tangent Graph Wave Vector Illustration vector illustration now. And search more of iStock's ...

The core idea behind NGMs is to utilize deep neural networks to parametrize probability functions over a given domain. This neural network can be trained efficiently by optimizing a loss function that ...

Graph Fourier transform (GFT) is an important tool for analyzing the irregular graph signals collected from various real-world networks. One of its applications is the graph Fourier transform ...