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11/25/2022
A Gaussian Process Regression based Dynamical Models Learning Algorithm for Target Tracking
Maneuvering target tracking is a challenging problem for sensor systems ...
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06/21/2022
Warm-Starting in Message Passing algorithms
Vector Approximate Message Passing (VAMP) provides the means of solving ...
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03/02/2022
Sketched RT3D: How to reconstruct billions of photons per second
Single-photon light detection and ranging (lidar) captures depth and int...
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11/25/2021
Robust Equivariant Imaging: a fully unsupervised framework for learning to image from noisy and partial measurements
Deep networks provide state-of-the-art performance in multiple imaging i...
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10/15/2021
Compressive Independent Component Analysis: Theory and Algorithms
Compressive learning forms the exciting intersection between compressed ...
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03/26/2021
Equivariant Imaging: Learning Beyond the Range Space
In various imaging problems, we only have access to compressed measureme...
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12/29/2020
COIN: Contrastive Identifier Network for Breast Mass Diagnosis in Mammography
Computer-aided breast cancer diagnosis in mammography is a challenging p...
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08/07/2020
Dual Convolutional Neural Networks for Breast Mass Segmentation and Diagnosis in Mammography
Deep convolutional neural networks (CNNs) have emerged as a new paradigm...
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07/28/2020
DeepMP for Non-Negative Sparse Decomposition
Non-negative signals form an important class of sparse signals. Many alg...
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06/27/2020
Compressive MR Fingerprinting reconstruction with Neural Proximal Gradient iterations
Consistency of the predictions with respect to the physical forward mode...
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12/05/2019
(l1,l2)-RIP and Projected Back-Projection Reconstruction for Phase-Only Measurements
This letter analyzes the performances of a simple reconstruction method,...
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11/25/2019
Deep Decomposition Learning for Inverse Imaging Problems
Deep learning is emerging as a new paradigm for solving inverse imaging ...
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10/22/2019
Compressive Learning for Semi-Parametric Models
In the compressive learning theory, instead of solving a statistical lea...
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06/30/2019
Signed Laplacian Deep Learning with Adversarial Augmentation for Improved Mammography Diagnosis
Computer-aided breast cancer diagnosis in mammography is limited by inad...
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03/01/2019
A Deep DUAL-PATH Network for Improved Mammogram Image Processing
We present, for the first time, a novel deep neural network architecture...
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11/11/2018
Analysis vs Synthesis with Structure - An Investigation of Union of Subspace Models on Graphs
We consider the problem of characterizing the `duality gap' between spar...
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11/11/2018
Analysis vs Synthesis - An Investigation of (Co)sparse Signal Models on Graphs
In this work, we present a theoretical study of signals with sparse repr...
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09/06/2018
Balanced multi-shot EPI for accelerated Cartesian MRF: An alternative to spiral MRF
The main purpose of this study is to show that a highly accelerated Cart...
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09/06/2018
CoverBLIP: scalable iterative matched filtering for MR Fingerprint recovery
Current proposed solutions for the high dimensionality of the MRF recons...
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09/05/2018
A deep learning approach for Magnetic Resonance Fingerprinting
Current popular methods for Magnetic Resonance Fingerprint (MRF) recover...
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08/28/2018
Learning Discriminative Representation with Signed Laplacian Restricted Boltzmann Machine
We investigate the potential of a restricted Boltzmann Machine (RBM) for...
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04/08/2018
Direct Estimation of Pharmacokinetic Parameters from DCE-MRI using Deep CNN with Forward Physical Model Loss
Dynamic contrast-enhanced (DCE) MRI is an evolving imaging technique tha...
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12/13/2017
Performance Analysis of Approximate Message Passing for Distributed Compressed Sensing
Bayesian approximate message passing (BAMP) is an efficient method in co...
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06/23/2017
Cover Tree Compressed Sensing for Fast MR Fingerprint Recovery
We adopt data structure in the form of cover trees and iteratively apply...
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03/22/2013