Tom Heskes

Tom Heskes

Radboud Universiteit

H-index: 55

Europe-Netherlands

About Tom Heskes

Tom Heskes, With an exceptional h-index of 55 and a recent h-index of 36 (since 2020), a distinguished researcher at Radboud Universiteit, specializes in the field of Machine Learning, Data Science, Deep Learning, Artificial Intelligence.

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

Pfeed: Generating near real-time personalized feeds using precomputed embedding similarities

How to evaluate uncertainty estimates in machine learning for regression?

Unsupervised anomaly detection algorithms on real-world data: how many do we need?

Tuning neural posterior estimation for gravitational wave inference

Heteroscedastic uncertainty quantification in Physics-Informed Neural Networks

Optimal training of mean variance estimation neural networks

Likelihood-ratio-based confidence intervals for neural networks

Graph Isomorphic Networks for Assessing Reliability of the Medium-Voltage Grid

Tom Heskes Information

University

Position

Professor of Computer Science and Artificial Intelligence

Citations(all)

13061

Citations(since 2020)

6506

Cited By

9170

hIndex(all)

55

hIndex(since 2020)

36

i10Index(all)

160

i10Index(since 2020)

92

Email

University Profile Page

Radboud Universiteit

Google Scholar

View Google Scholar Profile

Tom Heskes Skills & Research Interests

Machine Learning

Data Science

Deep Learning

Artificial Intelligence

Top articles of Tom Heskes

Title

Journal

Author(s)

Publication Date

Pfeed: Generating near real-time personalized feeds using precomputed embedding similarities

arXiv preprint arXiv:2402.16073

Binyam Gebre

Karoliina Ranta

Stef van den Elzen

Ernst Kuiper

Thijs Baars

...

2024/2/25

How to evaluate uncertainty estimates in machine learning for regression?

Neural Networks

Laurens Sluijterman

Eric Cator

Tom Heskes

2024/2/22

Unsupervised anomaly detection algorithms on real-world data: how many do we need?

Journal of Machine Learning Research

Roel Bouman

Zaharah Bukhsh

Tom Heskes

2024

Tuning neural posterior estimation for gravitational wave inference

arXiv preprint arXiv:2403.02443

Alex Kolmus

Justin Janquart

Tomasz Baka

Twan van Laarhoven

Chris Van Den Broeck

...

2024/3/4

Heteroscedastic uncertainty quantification in Physics-Informed Neural Networks

Olivier Claessen

Yuliya Shapovalova

Tom Heskes

2024/3/3

Optimal training of mean variance estimation neural networks

arXiv preprint arXiv:2302.08875

Laurens Sluijterman

Eric Cator

Tom Heskes

2023/2/17

Likelihood-ratio-based confidence intervals for neural networks

arXiv preprint arXiv:2308.02221

Laurens Sluijterman

Eric Cator

Tom Heskes

2023/8/4

Graph Isomorphic Networks for Assessing Reliability of the Medium-Voltage Grid

arXiv preprint arXiv:2310.01181

Charlotte Cambier van Nooten

Tom van de Poll

Sonja Füllhase

Jacco Heres

Tom Heskes

...

2023/10/2

Specialized versus generic allied health therapy and the risk of Parkinson's disease complications

Movement Disorders

Amir H Talebi

Jan HL Ypinga

Nienke M De Vries

Jorik Nonnekes

Marten Munneke

...

2023/2

Accessible Process Mining

Sven van der Post

Y Shapovalova

D Hiemstr

TM Heskes

2023/6/23

T72. AUTOENCODER BASED CORRECTION OF POPULATION STRATIFICATION PER INDIVIDUAL SNP'S

European Neuropsychopharmacology

Matthieu de Hemptinne

Danielle Posthuma

Tom Heskes

2023/10/1

AUTOENCODER BASED CORRECTION OF POPULATION STRATIFICATION PER INDIVIDUAL SNP'S

M de Hemptinne

D Posthuma

T Heskes

2023

Development and validation of the patient-reported “Facial Function Scale” for facioscapulohumeral muscular dystrophy

Disability and Rehabilitation

Karlien Mul

Feri Wijayanto

Tom GJ Loonen

Perry Groot

Sanne CC Vincenten

...

2023/4/24

Automatically detecting head-shakes in NGT conversations

Cas van Rijbroek

Martha Larson

Tom Heskes

2023/9

Structural modeling of clinical factors for simultaneous validation and prediction of future conversion to mild cognitive impairment

Alzheimer's & Dementia

Sebastiaan R Ram

Bryan A Strange

Linda Zhang

Teodoro Ser

Elizabeth Lucia Valeriano Lorenzo

...

2023/12

autoRasch: An R package to do semi-automated Rasch analysis

Applied Psychological Measurement

Feri Wijayanto

Ioan Gabriel Bucur

Perry Groot

Tom Heskes

2023/1

The effect of cardiovascular risk on disease progression in de novo Parkinson's disease patients: An observational analysis

Frontiers in Neurology

Max J Oosterwegel

Jesse H Krijthe

Melina GHE den Brok

Lieneke van den Heuvel

Edo Richard

...

2023/4/12

Semi-automated Rasch analysis with differential item functioning

Behavior Research Methods

Feri Wijayanto

Ioan Gabriel Bucur

Karlien Mul

Perry Groot

Baziel GM van Engelen

...

2023/9

Deterioration modeling of sewer pipes via discrete-time Markov chains: A large-scale case study in the Netherlands

arXiv preprint arXiv:2310.01888

Lisandro A Jimenez-Roa

Tom Heskes

Tiedo Tinga

H Molegraaf

Mariëlle Stoelinga

2023/10/3

Personalized monitoring of ambulatory function with a smartphone 2-minute walk test in multiple sclerosis

Multiple Sclerosis Journal

Ka-Hoo Lam

Ioan Gabriel Bucur

Pim Van Oirschot

Frank De Graaf

Eva Strijbis

...

2023/4

See List of Professors in Tom Heskes University(Radboud Universiteit)

Co-Authors

H-index: 121
D Posthuma

D Posthuma

Vrije Universiteit Amsterdam

H-index: 85
Ole Jensen

Ole Jensen

University of Birmingham

H-index: 76
Nico Karssemeijer

Nico Karssemeijer

Radboud Universiteit

H-index: 60
Stan Gielen

Stan Gielen

Radboud Universiteit

H-index: 52
Marcel van Gerven

Marcel van Gerven

Radboud Universiteit

H-index: 46
Hilbert Johan Kappen

Hilbert Johan Kappen

Radboud Universiteit

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