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A multi-label image classification framework based on GCN and adaptive knowledge graph
Official Implementation of "Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models".
[Paper][WWW2023] Structure Pre-training and Prompt Tuning for Knowledge Graph Transfer
kgTransformer: pre-training for reasoning over complex KG queries (KDD 22)
Few-Shot Image Classification with Knowledge Graph Ensembles
The code of paper Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs. Jiajun Chen, Huarui He, Feng Wu, Jie Wang. AAAI 2021.
Improving Inductive Link Prediction Using Hyper-Relational Facts
Source code for TACL paper "KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation".
IJCNN 2021: Inductive Learning on Commonsense Knowledge Graph Completion (Depreciated)
[Paper][ISWC 2021] Zero-shot Visual Question Answering using Knowledge Graph
The source code for "Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning".
Python code for predicting freight terminal capacity using knowledge graph embedding. This source code is developed in the research project LATULI.
The official implementation of "Empowering Spatial Knowledge Graph for Mobile Traffic Prediction" (Sigspatial'23)
Machine Learning method to predict the cardinality of conjunctive queries over knowledge graphs.
This project implements an emotion-based music recommendation system using computer vision, deep learning, and knowledge graph techniques. The system takes input from the user's facial features cap…
Predicting Cardiovascular disease using XGBoost and making Knowledge Graph using Neo4j_queries
KGANCDA is effective to predict associations between circRNA and cancer, which is based on knowledge graph attention network. The detail of the paper will be released in this page after the paper a…
Investigating the use of LLMs to populate knowledge graphs (KG) and then use KG to utilize predictive models
Predicting polypharmacy side-effects using knowledge graph embedding models.
李白 👤 作为唐代杰出诗人，其诗歌作品在中国文学史上具有重要地位。近年来，随着数字技术和人工智能的快速发展，传统文化普及推广的形式也面临着创新与变革。国内外对于李白诗歌的研究虽已相当深入，但在数字化、智能化普及方面仍存在不足。因此，本项目旨在通过构建李白知识图谱，结合大模型训练出专业的AI智能体，以生成式对话应用的形式，推动李白文化的普及与推广。
PlaNet: Predicting population response to drugs via clinical knowledge graph
DASFAA 2024 - Knowledge Graph (KG) Augmented Disease Prediction Code
This is the official github repo of Think-on-Graph (ICLR 2024). If you are interested in our work or willing to join our research team in Shenzhen, please feel free to contact us by email (xuchengj…
【三年面试五年模拟】AI算法工程师面试秘籍。涵盖AIGC、传统深度学习、自动驾驶、机器学习、计算机视觉、自然语言处理、SLAM、具身智能、元宇宙、AGI等AI行业面试笔试经验与干货知识。