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學術成果
【研究進展】BRB｜基于個體化腦網(wǎng)絡和腸網(wǎng)絡分析的精神分裂癥自動分類及生物學標志物研究

【摘要】華南理工大學生物醫(yī)學科學與工程學院吳凱教授與廣州醫(yī)科大學附屬腦科醫(yī)院吳逢春主任團隊合作，開展了基于個體化腦網(wǎng)絡和腸網(wǎng)絡分析的精神分裂癥自動分類及生物學標志物研究。2025年1月，《Brain Research Bulletin》雜志在線發(fā)表了題為《MO-GCN: A multi-omics graph convolutional network for discriminative ana

個人動態(tài)

吳凱 2025-01-17 1472
學術成果
推介文繼榮、趙鑫團隊力作《大語言模型》

近期，中國人民大學趙鑫教授和文繼榮教授領銜打造的《大語言模型》一書，由高等教育出版社正式上線發(fā)售。大語言模型（Large Language Model, LLM）是基于深度學習技術，尤其是變換器（Transformer）架構，通過大量的數(shù)據(jù)預訓練，能夠理解和生成自然語言的模型。該書匯聚了多位資深研究人員的智慧與經(jīng)驗，深入講解了預訓練、微調(diào)、對齊、提示工程等核心內(nèi)容，旨在為讀者提供系統(tǒng)性的語言模型知

個人動態(tài)

湯庸 2025-01-17 1634
學術論文
Enhanced Perception & Contextual Information Extraction Network for Dense Instance Segmentation

期刊/會議: IEEE Transactions on Image Processing, [CCF A, JCR Q1]

李鄉(xiāng)儒 2026.03 3842
學術論文
Boost dynamic community detection via exploiting member transition information

期刊/會議: Proceedings of the 30th International Conference on Database Systems for Advanced Applications (DASFAA25)

賀超波 2026.01 2655
學術論文
基于區(qū)塊鏈技術的再制造供應鏈公平?jīng)Q策研究

期刊/會議: 數(shù)學的實踐與認識

劉超 2026.05 1993

精選學術成果

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推薦學術成果

精選學術論文

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推薦學術論文

SCHOLAT開放數(shù)據(jù)

Anomaly Detection on Attributed Network

Community is the implicit structure in social networks. In academic social networks, the users with similar or same research interests are more likely to be in the same community with close links and similar attributes. Effective community detection results can be further utilized for user analytics and user recommendation.

User-Generated Item Recommendation

Anomaly detection on attributed networks is an important task in social network analysis. The goal is to find the anomalies that deviate significantly from the majority of the network in terms of some proximities, e.g. topological structure or attribute proximity. An effective anomaly detection can support many applications such as web spam detection, system fraud detection, network intrusion detection and representation learning.

SCHOLAT Interactive User Recommendation

Most of the existing recommendation methods assume that all the items are provided by separate producers, which is however not true in some recommendation tasks. That is, it is possible that some of the items are generated by users. Appropriately considering the user-item generation relation may bring benefit to some recommender systems, e.g., implicit recommender systems with only implicit user-item interactions.

SCHOLAT ScholarNet

The SCHOLAT Multiplex Network provides a comprehensive list of social information. In this network, we construct a multiplex structure with three layers: (1) The first layer represents connections between users who become friends. (2) The second layer represents connections between users who join the same groups. (3) The third layer represents connections between users who study the same courses. Furthermore, we define an individual ground-truth community based on the affiliation of users. All layers consist of the same 2,302 nodes with the highest quality. Each layer has a specific number of edges: 11,393 for the first layer, 139,004 for the second layer, and 70,226 for the third layer. We have divided these nodes into 11 communities.

開放數(shù)據(jù) - 通過SCHOLAT數(shù)據(jù)進一步推動你的研究

開放數(shù)據(jù)

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【研究進展】BRB｜ 基于個體化腦網(wǎng)絡和腸網(wǎng)絡分析的精神分裂癥自動分類及生物學標志物研究

推介文繼榮、趙鑫團隊力作《大語言模型》

Enhanced Perception & Contextual Information Extraction Network for Dense Instance Segmentation

Boost dynamic community detection via exploiting member transition information

基于區(qū)塊鏈技術的再制造供應鏈公平?jīng)Q策研究

精選學術成果

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精選學術論文

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SCHOLAT開放數(shù)據(jù)

Anomaly Detection on Attributed Network

User-Generated Item Recommendation

SCHOLAT Interactive User Recommendation

SCHOLAT ScholarNet

【研究進展】BRB｜基于個體化腦網(wǎng)絡和腸網(wǎng)絡分析的精神分裂癥自動分類及生物學標志物研究

推介文繼榮、趙鑫團隊力作《大語言模型》