Erik J Bekkers

Erik J Bekkers

Universiteit van Amsterdam

H-index: 23

Europe-Netherlands

About Erik J Bekkers

Erik J Bekkers, With an exceptional h-index of 23 and a recent h-index of 19 (since 2020), a distinguished researcher at Universiteit van Amsterdam, specializes in the field of machine learning, medical image analysis, computer vision, differential geometry, Lie groups.

His recent articles reflect a diverse array of research interests and contributions to the field:

Dynamic prediction of malignant ventricular arrhythmias using neural networks in patients with an implantable cardioverter-defibrillator

Generating Cerebral Vessel Trees of Acute Ischemic Stroke Patients using Conditional Set-Diffusion

Uncertainty-aware retinal layer segmentation in OCT through probabilistic signed distance functions

Latent Field Discovery In Interacting Dynamical Systems With Neural Fields

An Exploration of Conditioning Methods in Graph Neural Networks

Learned Gridification for Efficient Point Cloud Processing

Regular SE (3) Group Convolutions for Volumetric Medical Image Analysis

PDE-based group equivariant convolutional neural networks

Erik J Bekkers Information

University

Position

___

Citations(all)

2072

Citations(since 2020)

1697

Cited By

881

hIndex(all)

23

hIndex(since 2020)

19

i10Index(all)

33

i10Index(since 2020)

31

Email

University Profile Page

Universiteit van Amsterdam

Google Scholar

View Google Scholar Profile

Erik J Bekkers Skills & Research Interests

machine learning

medical image analysis

computer vision

differential geometry

Lie groups

Top articles of Erik J Bekkers

Title

Journal

Author(s)

Publication Date

Dynamic prediction of malignant ventricular arrhythmias using neural networks in patients with an implantable cardioverter-defibrillator

Ebiomedicine

Maarten ZH Kolk

Samuel Ruipérez-Campillo

Laura Alvarez-Florez

Brototo Deb

Erik J Bekkers

...

2024/1/1

Generating Cerebral Vessel Trees of Acute Ischemic Stroke Patients using Conditional Set-Diffusion

Thijs P Kuipers

Praneeta R Konduri

Henk Marquering

Erik J Bekkers

2024/2/13

Uncertainty-aware retinal layer segmentation in OCT through probabilistic signed distance functions

Mohammad Mohaiminul Islam

Coen de Vente

Bart Liefers

Caroline Klaver

Erik J Bekkers

...

2024/2/13

Latent Field Discovery In Interacting Dynamical Systems With Neural Fields

Advances in Neural Information Processing Systems

Miltiadis Miltos Kofinas

Erik Bekkers

Naveen Nagaraja

Efstratios Gavves

2024/2/13

An Exploration of Conditioning Methods in Graph Neural Networks

arXiv preprint arXiv:2305.01933

Yeskendir Koishekenov

Erik J Bekkers

2023/5/3

Learned Gridification for Efficient Point Cloud Processing

arXiv preprint arXiv:2307.14354

Putri A Van der Linden

David W Romero

Erik J Bekkers

2023/7/22

Regular SE (3) Group Convolutions for Volumetric Medical Image Analysis

Thijs P Kuipers

Erik J Bekkers

2023/10/1

PDE-based group equivariant convolutional neural networks

Journal of Mathematical Imaging and Vision

Bart MN Smets

Jim Portegies

Erik J Bekkers

Remco Duits

2023/1

E (n) Equivariant Message Passing Simplicial Networks

arXiv preprint arXiv:2305.07100

Floor Eijkelboom1 Rob Hesselink

Erik Bekkers

2023/5

Artificial intelligence for science in quantum, atomistic, and continuum systems

arXiv preprint arXiv:2307.08423

Xuan Zhang

Limei Wang

Jacob Helwig

Youzhi Luo

Cong Fu

...

2023/7/17

On genuine invariance learning without weight-tying

Artem Moskalev

Anna Sepliarskaia

Erik J Bekkers

Arnold WM Smeulders

2023/9/27

Improving generalizability for MHC-I binding peptide predictions through geometric deep learning

bioRxiv

Dario F Marzella

Giulia Crocioni

Tadija Radusinović

Daniil Lepikhov

Heleen Severin

...

2023/12/5

SE (3) Group Convolutional Neural Networks and a Study on Group Convolutions and Equivariance for DWI Segmentation

Renfei Liu

Francois Lauze

Erik Bekkers

Kenny Erleben

Sune Darkner

2023/3/2

E Equivariant Message Passing Simplicial Networks

Floor Eijkelboom

Rob Hesselink

Erik J Bekkers

2023/7/3

Can strong structural encoding reduce the importance of Message Passing?

Floor Eijkelboom

Erik J Bekkers

Michael M Bronstein

Francesco Di Giovanni

2023/9/27

Visual Scene Representation with Hierarchical Equivariant Sparse Coding

Christian A Shewmake

Domas Buracas

Hansen Lillemark

Jinho Shin

Erik J Bekkers

...

2023/11/29

Modelling Long Range Dependencies in D: From Task-Specific to a General Purpose CNN

arXiv preprint arXiv:2301.10540

David M Knigge

David W Romero

Albert Gu

Efstratios Gavves

Erik J Bekkers

...

2023/1/25

Improved patient selection for primary prevention ICD implantation by predicting ICD non-benefit using artificial intelligence

Europace

MZH Kolk

S Ruiperez-Campillo

B Deb

EJ Bekkers

BD De Vos

...

2023/6

Optimising Patient Selection for Primary Prevention ICD Implantation: Utilising Multimodal Machine Learning to Assess Risk of ICD Non-Benefit.

Europace: European Pacing, Arrhythmias, and Cardiac Electrophysiology: Journal of the Working Groups on Cardiac Pacing, Arrhythmias, and Cardiac Cellular Electrophysiology of the European Society of Cardiology

MZH Kolk

S Ruipérez-Campillo

B Deb

E Bekkers

CP Allaart

...

2023/9/15

Fast, Expressive Equivariant Networks through Weight-Sharing in Position-Orientation Space

Erik J Bekkers

Sharvaree Vadgama

Rob Hesselink

Putri A Van der Linden

David W Romero

2023/10/13

See List of Professors in Erik J Bekkers University(Universiteit van Amsterdam)