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Dongdong Chen 陈东东
Research Associate The University of Edinburgh, Edinburgh, UK |
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I am a Postdoctoral Research Associate on Computational Sensing and Machine Learning working with Prof. Mike Davies in the University of Edinburgh. Before that, I received my PhD in computer science from Sichuan University in 2017, under the supervision of Prof. Jiancheng Lv. My research interests are machine learning, deep learning, computational imaging, and inverse problems. |
Selected Publications
Sensing Theorems for Unsupervised Learning in Linear Inverse Problems |
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Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning |
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Unsupervised Learning From Incomplete Measurements for Inverse Problems |
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Robust Equivariant Imaging: a fully unsupervised framework for learning to image from noisy and partial measurements |
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Equivariant Imaging: Learning Beyond the Range Space |
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Dual Convolutional Neural Networks for Breast Mass Segmentation and Diagnosis in Mammography |
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Deep Decomposition Learning for Inverse Imaging Problems |
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Compressive MRF reconstruction with neural proximal gradient iterations |
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COIN: Contrastive Identifier Network for Breast Mass Diagnosis in Mammography |
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An Improved Dual-Channel Network to Eliminate Catastrophic Forgetting |
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A Network Framework For Small-Sample Learning |
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Signed Laplacian Deep Learning with Adversarial Augmentation for Improved Mammography Diagnosis |
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Deep Fully Convolutional Network for MR Fingerprinting |
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Spatio-temporal regularization for deep MR Fingerprinting |
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A fully convolutional network for MR Fingerprinting |
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Deep learning for Magnetic Resonance Fingerprinting |
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A Deep Dual-Path Network For Improved Mammogram Image Processing |
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Geometriy of Deep Learning for Magnetic Resonance Fingerprinting |
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Learning Discriminative Representation with Signed Laplacian Restricted Boltzmann Machine |
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A deep learning approach for Magnetic Resonance Fingerprinting |
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Improved Breast Mass Segmentation in Mammograms with Conditional Residual U-net |
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Graph regularized Restricted Boltzmann Machines |
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Angle-based Embedding Quality Assessment Method for Manifold Learning |
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Unsupervised Multi-Manifold Clustering by Learning Deep Representation |
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Angle-based Outlier Detection Algorithm with More Stable Relationships |
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A Local Non-negative Pursuit Method for Intrinsic Manifold Structure Preservation |
Awards and Honors
MICCAI'18 BIA Best Paper Nomination, 2018
Sichuan University Outstanding Graduate Student, 2017
National Scholarship, 2014
Academic Activities
Journal reviewer: IJCV, IEEE TNNLS, IEEE TIP, IEEE TMI, IEEE TCYB, IEEE TSMCS, IEEE TIM, IEEE TCBB, INFO, PRL, MedIA, EL, NEUCOM, etc.
Conf. PC member: VISAPP'20, VISAPP'21, MICCAI'20, MICAAI'21, MICCAI'22, AAAI'21, AAAI'22, ICML'22, NeurIPS'22, CVPR'23, ICML'23, etc.
Last update: Mar. 2022
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