Mike E. Davies | DeepAI

DeepAI AI Chat

Featured Co-authors

Dongdong Chen
113 publications
Jiancheng Lv
46 publications
Laurent Jacques
39 publications
Bjoern H. Menze
31 publications
Luc Vandendorpe
16 publications
Mohammad Golbabaee
14 publications
Julián Tachella
10 publications
Heyi Li
8 publications
Giles Tetteh
8 publications
Mehrdad Yaghoobi
8 publications
Marion I. Menzel
8 publications

∙ 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 ...

0 Mengwei Sun, et al. ∙

∙ 06/21/2022

Warm-Starting in Message Passing algorithms

Vector Approximate Message Passing (VAMP) provides the means of solving ...

0 Nikolajs Skuratovs, et al. ∙

∙ 03/02/2022

Sketched RT3D: How to reconstruct billions of photons per second

Single-photon light detection and ranging (lidar) captures depth and int...

0 Julián Tachella, et al. ∙

∙ 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...

3 Dongdong Chen, et al. ∙

∙ 10/15/2021

Compressive Independent Component Analysis: Theory and Algorithms

Compressive learning forms the exciting intersection between compressed ...

0 Michael P. Sheehan, et al. ∙

∙ 03/26/2021

Equivariant Imaging: Learning Beyond the Range Space

In various imaging problems, we only have access to compressed measureme...

10 Dongdong Chen, et al. ∙

∙ 12/29/2020

COIN: Contrastive Identifier Network for Breast Mass Diagnosis in Mammography

Computer-aided breast cancer diagnosis in mammography is a challenging p...

22 Heyi Li, et al. ∙

∙ 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...

0 Heyi Li, et al. ∙

∙ 07/28/2020

DeepMP for Non-Negative Sparse Decomposition

Non-negative signals form an important class of sparse signals. Many alg...

0 Konstantinos A. Voulgaris, et al. ∙

∙ 06/27/2020

Compressive MR Fingerprinting reconstruction with Neural Proximal Gradient iterations

Consistency of the predictions with respect to the physical forward mode...

39 Dongdong Chen, et al. ∙

∙ 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,...

0 Thomas Feuillen, et al. ∙

∙ 11/25/2019

Deep Decomposition Learning for Inverse Imaging Problems

Deep learning is emerging as a new paradigm for solving inverse imaging ...

0 Dongdong Chen, et al. ∙

∙ 10/22/2019

Compressive Learning for Semi-Parametric Models

In the compressive learning theory, instead of solving a statistical lea...

0 Michael P. Sheehan, et al. ∙

∙ 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...

0 Heyi Li, et al. ∙

∙ 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...

0 Heyi Li, et al. ∙

∙ 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...

0 Madeleine S. Kotzagiannidis, et al. ∙

∙ 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...

0 Madeleine S. Kotzagiannidis, et al. ∙

∙ 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...

0 Arnold Julian Vinoj Benjamin, et al. ∙

∙ 09/06/2018

CoverBLIP: scalable iterative matched filtering for MR Fingerprint recovery

Current proposed solutions for the high dimensionality of the MRF recons...

0 Mohammad Golbabaee, et al. ∙

∙ 09/05/2018

A deep learning approach for Magnetic Resonance Fingerprinting

Current popular methods for Magnetic Resonance Fingerprint (MRF) recover...

0 Mohammad Golbabaee, et al. ∙

∙ 08/28/2018

Learning Discriminative Representation with Signed Laplacian Restricted Boltzmann Machine

We investigate the potential of a restricted Boltzmann Machine (RBM) for...

0 Dongdong Chen, et al. ∙

∙ 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...

0 Cagdas Ulas, et al. ∙

∙ 12/13/2017

Performance Analysis of Approximate Message Passing for Distributed Compressed Sensing

Bayesian approximate message passing (BAMP) is an efficient method in co...

0 Gabor Hannak, et al. ∙

∙ 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...

0 Mohammad Golbabaee, et al. ∙

∙ 03/22/2013

Sample Distortion for Compressed Imaging

We propose the notion of a sample distortion (SD) function for independe...

0 Chunli Guo, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world