Yue Y, Lin F, Guanyi Mou, Zhang Z, Understanding Hyperbolic Metric Learning through Hard Negative Sampling. In Proceeding of Winter Conference on Applications of Computer Vision (WACV), 2024.

Lin F, Yue Y, Zhang Z, Hou S, Yamada KD, Kolachalama VB, Saligrama V, InfoCD: A Contrastive Chamfer Distance Loss for Point Cloud Completion. In Proceeding of Advances in Neural Information Processing Systems (NeurIPS), 2023.

Lin F, Yue Y, Hou S, Yu X, Xu Y, Yamada KD, Zhang Z, Hyperbolic Chamfer Distance for Point Cloud Completion. In Proceeding of International Conference on Computer Vision (ICCV), 2023.

Yamada KD, Baladram MS, Lin F, Relation is an option for processing context information, Frontiers in Artificial Intelligence, 5:924688, 2022.

Gao C, Cai G, Jiang X, Zheng F, Zhang J, Gong Y, Lin F, Sun X, Bai X. Conditional Feature Learning based Transformer for Text-Based Person Search. IEEE Transactions on Image Processing. 2022 Sep 14.

Lin F, Xu Y, Zhang Z, Gao C, Yamada KD, Cosmos Propagation Network: Deep Learning Model for Point Cloud Completion, Neurocomputing, 507:221-234, 2022.

Yamada KD, Baladram MS, Lin F, Progress in research on implementing machine consciousness, Interdisciplinary Information Sciences, 28(1):95-105, 2022.

Xu Y, Arai S, Liu D, Lin F, & Kosuge K. FPCC: Fast Point Cloud Clustering-based Instance Segmentation for Industrial Bin-picking. Neurocomputing, 2022, ISSN 0925-2312.

Lin F, Gao C, Yamada KD, An effective convolutional neural network for visualized understanding transboundary air pollution based on Himawari-8 satellite images, IEEE Geoscience and Remote Sensing Letters, 2021, 19, 1-5.

Yamada KD, Lin F, Nakamura T, Developing a novel recurrent neural network architecture with fewer parameters and good learning performance, Interdisciplinary Information Sciences, 27(1):25-40, 2021.

Xu Y, Arai S, Liu D, Lin F, & Kosuge K. (2020). FPCC: Fast Point Cloud Clustering for Instance Segmentation. arXiv preprint arXiv:2012.14618.

Yue Y, Lin F, Yamada KD, & Zhang Z. (2023). Hyperbolic contrastive learning. arXiv preprint arXiv:2302.01409.