
Deep Interactive Denoiser (DID) for XRay Computed Tomography
Low dose computed tomography (LDCT) is desirable for both diagnostic ima...
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Feature Space Singularity for OutofDistribution Detection
OutofDistribution (OoD) detection is important for building safe artif...
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MetaMgNet: Meta Multigrid Networks for Solving Parameterized Partial Differential Equations
This paper studies numerical solutions for parameterized partial differe...
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Penalty and Augmented Lagrangian Methods for Layerparallel Training of Residual Networks
Algorithms for training residual networks (ResNets) typically require fo...
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Transferred Discrepancy: Quantifying the Difference Between Representations
Understanding what information neural networks capture is an essential p...
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Learning to Scan: A Deep Reinforcement Learning Approach for Personalized Scanning in CT Imaging
Computed Tomography (CT) takes Xray measurements on the subjects to rec...
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RODENet: Learning Ordinary Differential Equations with Randomness from Data
Random ordinary differential equations (RODEs), i.e. ODEs with random pa...
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MetaInvNet: Meta Inversion Network for Sparse View CT Image Reconstruction
Xray Computed Tomography (CT) is widely used in clinical applications s...
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Enhancing Certified Robustness of Smoothed Classifiers via Weighted Model Ensembling
Randomized smoothing has achieved stateoftheart certified robustness ...
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Blind Adversarial Training: Balance Accuracy and Robustness
Adversarial training (AT) aims to improve the robustness of deep learnin...
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Distillation ≈ Early Stopping? Harvesting Dark Knowledge Utilizing Anisotropic Information Retrieval For Overparameterized Neural Network
Distillation is a method to transfer knowledge from one model to another...
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AnnotationFree Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images
Segmenting coronary arteries is challenging, as classic unsupervised met...
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A Review on Deep Learning in Medical Image Reconstruction
Medical imaging is crucial in modern clinics to guide the diagnosis and ...
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Understanding and Improving Transformer From a MultiParticle Dynamic System Point of View
The Transformer architecture is widely used in natural language processi...
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NPTCnet: NarrowBand Parallel Transport Convolutional Neural Network on Point Clouds
Convolution plays a crucial role in various applications in signal and i...
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Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning
Conservation laws are considered to be fundamental laws of nature. It ha...
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You Only Propagate Once: Accelerating Adversarial Training Using Maximal Principle
Deep learning achieves stateoftheart results in many areas. However r...
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You Only Propagate Once: Painless Adversarial Training Using Maximal Principle
Deep learning achieves stateoftheart results in many areas. However r...
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CURE: Curvature Regularization For Missing Data Recovery
Missing data recovery is an important and yet challenging problem in ima...
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JSRNet: A Deep Network for Joint SpatialRadon Domain CT Reconstruction from incomplete data
CT image reconstruction from incomplete data, such as sparse views and l...
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PDENet 2.0: Learning PDEs from Data with A NumericSymbolic Hybrid Deep Network
Partial differential equations (PDEs) are commonly derived based on empi...
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Whole Brain Susceptibility Mapping Using Harmonic Incompatibility Removal
Quantitative susceptibility mapping (QSM) uses the phase data in magneti...
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Parallel Transport Convolution: A New Tool for Convolutional Neural Networks on Manifolds
Convolution has been playing a prominent role in various applications in...
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Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration
In this paper, we propose a new control framework called the moving endp...
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Nostalgic Adam: Weighing more of the past gradients when designing the adaptive learning rate
Firstorder optimization methods have been playing a prominent role in d...
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Distributed Caching for Complex Querying of Raw Arrays
As applications continue to generate multidimensional data at exponenti...
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EndtoEnd Abnormality Detection in Medical Imaging
Nearly all of the deep learning based image analysis methods work on rec...
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Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
In our work, we bridge deep neural network design with numerical differe...
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PDENet: Learning PDEs from Data
In this paper, we present an initial attempt to learn evolution PDEs fro...
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An Edge Driven Wavelet Frame Model for Image Restoration
Wavelet frame systems are known to be effective in capturing singulariti...
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Building a comprehensive syntactic and semantic corpus of Chinese clinical texts
Objective: To build a comprehensive corpus covering syntactic and semant...
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Image Restoration: A General Wavelet Frame Based Model and Its Asymptotic Analysis
Image restoration is one of the most important areas in imaging science....
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ℓ_0 Minimization for Wavelet Frame Based Image Restoration
The theory of (tight) wavelet frames has been extensively studied in the...
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Bin Dong
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