Yu Tian

Orcid: 0000-0001-5533-7506

Affiliations:
  • Harvard University, Harvard Medical School, Cambridge, MA, USA
  • University of Adelaide, Institute of Machine Learning, Adelaide, Australia (PhD 2022)


According to our database1, Yu Tian authored at least 41 papers between 2019 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
FairCLIP: Harnessing Fairness in Vision-Language Learning.
CoRR, 2024

2023
Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images.
Medical Image Anal., December, 2023

Artifact-Tolerant Clustering-Guided Contrastive Embedding Learning for Ophthalmic Images in Glaucoma.
IEEE J. Biomed. Health Informatics, September, 2023

FairSeg: A Large-scale Medical Image Segmentation Dataset for Fairness Learning with Fair Error-Bound Scaling.
CoRR, 2023

AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection.
CoRR, 2023

Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection.
CoRR, 2023

Harvard Eye Fairness: A Large-Scale 3D Imaging Dataset for Equitable Eye Diseases Screening and Fair Identity Scaling.
CoRR, 2023

Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Identity Normalization.
CoRR, 2023

Semantic Role Labeling Guided Out-of-distribution Detection.
CoRR, 2023

BRAIxDet: Learning to Detect Malignant Breast Lesion with Incomplete Annotations.
CoRR, 2023

Asymmetric Co-teaching with Multi-view Consensus for Noisy Label Learning.
CoRR, 2023

Unsupervised Anomaly Detection in Medical Images with a Memory-Augmented Multi-level Cross-Attentional Masked Autoencoder.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023

Learning Support and Trivial Prototypes for Interpretable Image Classification.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Harvard Glaucoma Detection and Progression: A Multimodal Multitask Dataset and Generalization-Reinforced Semi-Supervised Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

BoMD: Bag of Multi-label Descriptors for Noisy Chest X-ray Classification.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification Generalisation.
CoRR, 2022

Artifact-Tolerant Clustering-Guided Contrastive Embedding Learning for Ophthalmic Images.
CoRR, 2022

Translation Consistent Semi-supervised Segmentation for 3D Medical Images.
CoRR, 2022

Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder.
CoRR, 2022

Semantic-guided Image Virtual Attribute Learning for Noisy Multi-label Chest X-ray Classification.
CoRR, 2022

Knowledge Distillation to Ensemble Global and Interpretable Prototype-Based Mammogram Classification Models.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Contrastive Transformer-Based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

NVUM: Non-volatile Unbiased Memory for Robust Medical Image Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification Generalisation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Pixel-Wise Energy-Biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes.
Proceedings of the Computer Vision - ECCV 2022, 2022

ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Deep One-Class Classification via Interpolated Gaussian Descriptor.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
ACPL: Anti-curriculum Pseudo-labelling forSemi-supervised Medical Image Classification.
CoRR, 2021

Multi-centred Strong Augmentation via Contrastive Learning for Unsupervised Lesion Detection and Segmentation.
CoRR, 2021

Noisy Label Learning for Large-scale Medical Image Classification.
CoRR, 2021

Unsupervised Anomaly Detection and Localisation with Multi-scale Interpolated Gaussian Descriptors.
CoRR, 2021

Weakly-supervised Video Anomaly Detection with Contrastive Learning of Long and Short-range Temporal Features.
CoRR, 2021

Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep Learning.
CoRR, 2021

Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Self-supervised Mean Teacher for Semi-supervised Chest X-Ray Classification.
Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021

Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Photoshopping Colonoscopy Video Frames.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019
One-Stage Five-Class Polyp Detection and Classification.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019


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