Jinfa Yang

Orcid: 0000-0001-6138-7569

According to our database1, Jinfa Yang authored at least 12 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
Tensor decompositions for temporal knowledge graph completion with time perspective.
Expert Syst. Appl., March, 2024

VPDETR: End-to-End Vanishing Point DEtection TRansformers.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Improving point cloud classification and segmentation via parametric veronese mapping.
Pattern Recognit., December, 2023

Employing Latent Categories of Entities for Knowledge Graph Embeddings With Contrastive Learning.
IEEE Robotics Autom. Lett., June, 2023

Cross-Modal Contrastive Learning for Domain Adaptation in 3D Semantic Segmentation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

ECO-3D: Equivariant Contrastive Learning for Pre-training on Perturbed 3D Point Cloud.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Deep Unsupervised Domain Adaptation with Time Series Sensor Data: A Survey.
Sensors, 2022

Transformer Based Line Segment Classifier with Image Context for Real-Time Vanishing Point Detection in Manhattan World.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Learning Hierarchy-Aware Quaternion Knowledge Graph Embeddings with Representing Relations as 3D Rotations.
Proceedings of the 29th International Conference on Computational Linguistics, 2022

Knowledge Graph Embedding by Adaptive Limit Scoring Loss Using Dynamic Weighting Strategy.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021
Improving Knowledge Graph Embedding Using Affine Transformations of Entities Corresponding to Each Relation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

2020
Deep Shape from Polarization.
Proceedings of the Computer Vision - ECCV 2020, 2020


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