2026 Hilbert J. Kappen: Engineering and Technology Researcher – H-Index, Publications & Awards

D-Index & Metrics

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Engineering and Technology	40	7264	7011	143	138	203	7124

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Engineering and Technology

7264

7011

143

138

203

7124

Engineering and Technology

D-Index

Citations

7124

World Ranking

7264

National Ranking

143

Overview

Hilbert J. Kappen is affiliated with Radboud University in the Netherlands. Their research spans multiple disciplines within computer science and physics, focusing strongly on artificial intelligence and quantum computing.

The primary fields of study for Kappen include:

Computer Science
Physics and Astronomy

Their work covers various subfields, prominently featuring:

Artificial Intelligence
Atomic and Molecular Physics, and Optics
Electrical and Electronic Engineering
Genetics
Cognitive Neuroscience

Within these domains, Kappen's research addresses key topics such as:

Quantum Computing Algorithms and Architecture
Quantum Information and Cryptography
Advanced Memory and Neural Computing
Neural Networks and Reservoir Computing
Quantum many-body systems
Cold Atom Physics and Bose-Einstein Condensates
Neural dynamics and brain function

Kappen has contributed to a range of publication venues. These include:

arXiv (Cornell University)
Journal of Physics A Mathematical and Theoretical
Nature Nanotechnology
Machine Learning Science and Technology
Genetics Selection Evolution

Among their recent papers are:

An atomic Boltzmann machine capable of self-adaption, 2021, Nature Nanotechnology
Bayesian neural networks with variable selection for prediction of genotypic values, 2020, Genetics Selection Evolution
Learning quantum models from quantum or classical data, 2020, Journal of Physics A Mathematical and Theoretical
Training quantum Boltzmann machines with the β-variational quantum eigensolver, 2024, Machine Learning Science and Technology
Why adiabatic quantum annealing is unlikely to yield speed-up, 2023, Journal of Physics A Mathematical and Theoretical

Kappen frequently collaborates with a consistent group of co-authors including:

Werner M. J. van Weerdenburg
Alexander A. Khajetoorians
Peyman Najafi
Aarón Villanueva
Eduardo Domínguez

Best Publications

Practical confidence and prediction intervals for prediction tasks

T. Heskes;W.A.J.J. Wiegerinck;H.J. Kappen

417
Citations
Path integrals and symmetry breaking for optimal control theory

H J Kappen

376
Citations
Optimal control as a graphical model inference problem

Hilbert J. Kappen;Vicenç Gómez;Manfred Opper

375
Citations
Linear theory for control of nonlinear stochastic systems.

Hilbert J. Kappen

356
Citations
Sufficient Conditions for Convergence of the Sum–Product Algorithm

J.M. Mooij;H.J. Kappen

297
Citations
On tempo tracking: Tempogram Representation and Kalman filtering

Ali Taylan Cemgil;Bert Kappen;Peter Desain;Henkjan Honing

293
Citations
Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment

K. N. McGuire;C. De Wagter;K. Tuyls;H. J. Kappen

256
Citations
Efficient learning in Boltzmann machines using linear response theory

H. J. Kappen;F. B. Rodríguez

251
Citations
Efficient Optical Flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Drone

Kimberly McGuire;Guido de Croon;Christophe De Wagter;Karl Tuyls

217
Citations
Optimal control as a graphical model inference problem

B. Kappen;V. Gomez;M. Opper

200
Citations
Minimax PAC bounds on the sample complexity of reinforcement learning with a generative model

Mohammad Gheshlaghi Azar;Rémi Munos;Hilbert J. Kappen

185
Citations
A generative model for music transcription

A.T. Cemgil;H.J. Kappen;D. Barber

169
Citations
An introduction to stochastic control theory, path integrals and reinforcement learning

Hilbert J. Kappen

169
Citations
Associative memory with dynamic synapses

Lovorka Pantic;Joaquín J. Torres;Hilbert J. Kappen;Stan C. A. M. Gielen

140
Citations
Dynamic policy programming

Mohammad Gheshlaghi Azar;Vicenç Gómez;Hilbert J. Kappen

131
Citations
On-line learning processes in artificial neural networks

T. Heskes;H.J. Kappen

129
Citations
Speedy Q-Learning

Mohammad Ghavamzadeh;Hilbert J. Kappen;Mohammad G. Azar;Rémi Munos

119
Citations
Learning Universal Computations with Spikes.

Dominik Thalmeier;Marvin Uhlmann;Marvin Uhlmann;Hilbert J. Kappen;Raoul-Martin Memmesheimer;Raoul-Martin Memmesheimer

103
Citations
Adaptive Importance Sampling for Control and Inference

Hilbert Johan Kappen;Hans Christian Ruiz

95
Citations
On the use of interaction error potentials for adaptive brain computer interfaces

A. Llera;M. A. J. van Gerven;V. Gómez;O. Jensen

83
Citations
Path integral control and state-dependent feedback.

Sep Thijssen;H. J. Kappen

82
Citations
Sufficient conditions for convergence of Loopy Belief Propagation

Joris M. Mooij;Hilbert J. Kappen

81
Citations
On the properties of the Bethe approximation and loopy belief propagation on binary networks

J M Mooij;H J Kappen

78
Citations