Zehao Niu

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1ranked-venue papers

1as first author

1since 2021 · last 2023

—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence

1 paper

Graph learning · 46% Probabilistic and Bayesian machine learning · 46% Learning paradigms · 7%

Topics — the 5 heaviest of 5, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Machine learning › Probabilistic and Bayesian machine learning › stochastic processes gaussian process	0.7	1	2023	Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning · ICLR 2023
Machine learning › Probabilistic and Bayesian machine learning › stochastic processes › gaussian process graph gaussian processes	0.7	1	2023	Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning · ICLR 2023
Machine learning › Graph learning graph kernel	0.7	1	2023	Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning · ICLR 2023
Machine learning › Graph learning graph neural network	0.7	1	2023	Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning · ICLR 2023
Machine learning › Learning paradigms semi-supervised learning	0.2	1	2023	Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning · ICLR 2023

Methods — techniques the papers use, named apart from their topics

graph neural network · 0.7gaussian process · 0.7

Year	Publication	Venue	Position
2023	Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning Zehao Niu, Mihai Anitescu, Jie Chen 0007	ICLR	1