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Zhaozhi Li

dblp:306/7922 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2024
—ORCID · unresolved

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

Artificial intelligence and machine learning · 2 · 2 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
Probabilistic and Bayesian machine learning · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Probabilistic and Bayesian machine learning › stochastic processes
gaussian process
0.712023
Semi-Parametric Inducing Point Networks and Neural Processes · ICLR 2023
Machine learning › Probabilistic and Bayesian machine learning › stochastic processes › gaussian process
inducing point methods
0.712023
Semi-Parametric Inducing Point Networks and Neural Processes · ICLR 2023
Machine learning › Probabilistic and Bayesian machine learning › stochastic processes › gaussian process
neural processes
0.712023
Semi-Parametric Inducing Point Networks and Neural Processes · ICLR 2023
Machine learning › Probabilistic and Bayesian machine learning › statistical inference
semiparametric model
0.212023
Semi-Parametric Inducing Point Networks and Neural Processes · ICLR 2023

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

neural processes · 0.7inducing points · 0.7
YearPublicationVenuePosition
2024 An integrated framework for accurate trajectory prediction based on deep learning
Zhaozhi Li, Zikun Zhu, Charles Chang, Ying-Chi Chen
Appl. Intell.2
2023 Semi-Parametric Inducing Point Networks and Neural Processes
Richa Rastogi, Yair Schiff, Alon Hacohen, Zhaozhi Li, Ian Lee, Yuntian Deng, Mert R. Sabuncu, Volodymyr Kuleshov
ICLR4