Tim C Kietzmann

Tim C Kietzmann

Radboud Universiteit

H-index: 23

Europe-Netherlands

About Tim C Kietzmann

Tim C Kietzmann, With an exceptional h-index of 23 and a recent h-index of 20 (since 2020), a distinguished researcher at Radboud Universiteit, specializes in the field of cognitive computational neuroscience, vision, machine learning, deep learning, computational modeling.

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

Computational characterization of the role of an attention schema in controlling visuospatial attention

Diagnosing Catastrophe: Large parts of accuracy loss in continual learning can be accounted for by readout misalignment

Scene representations underlying categorization behaviour emerge 100 to 200 ms after stimulus onset

Keep moving: sensorimotor integration of fixational eye-movements yields human-like superresolution in recurrent neural networks

High-level prediction errors in low-level visual cortex

Balancing stability and plasticity in continual learning: the readout-decomposition of activation change (RDAC) framework

The neuroconnectionist research programme

Characterising representation dynamics in recurrent neural networks for object recognition

Tim C Kietzmann Information

University

Position

Donders Institute for Brain Cognition and Behaviour

Citations(all)

2588

Citations(since 2020)

2143

Cited By

929

hIndex(all)

23

hIndex(since 2020)

20

i10Index(all)

35

i10Index(since 2020)

30

Email

University Profile Page

Radboud Universiteit

Google Scholar

View Google Scholar Profile

Tim C Kietzmann Skills & Research Interests

cognitive computational neuroscience

vision

machine learning

deep learning

computational modeling

Top articles of Tim C Kietzmann

Title

Journal

Author(s)

Publication Date

Computational characterization of the role of an attention schema in controlling visuospatial attention

arXiv preprint arXiv:2402.01056

Lotta Piefke

Adrien Doerig

Tim Kietzmann

Sushrut Thorat

2024/2/1

Diagnosing Catastrophe: Large parts of accuracy loss in continual learning can be accounted for by readout misalignment

arXiv preprint arXiv:2310.05644

Daniel Anthes

Sushrut Thorat

Peter König

Tim C Kietzmann

2023/10/9

Scene representations underlying categorization behaviour emerge 100 to 200 ms after stimulus onset

Journal of Vision

Agnessa Karapetian

Antoniya Boyanova

Muthukumar Pandaram

Klaus Obermayer

Tim C Kietzmann

...

2023/8/1

Keep moving: sensorimotor integration of fixational eye-movements yields human-like superresolution in recurrent neural networks

Adrien Doerig

Kirubeswaran OR

Tim C Kietzmann

2023

High-level prediction errors in low-level visual cortex

bioRxiv

David Richter

Tim C Kietzmann

Floris P de Lange

2023

Balancing stability and plasticity in continual learning: the readout-decomposition of activation change (RDAC) framework

arXiv preprint arXiv:2310.04741

Daniel Anthes

Sushrut Thorat

Tim C Kietzmann

Peter König

2023/10/7

The neuroconnectionist research programme

Adrien Doerig

Rowan P Sommers

Katja Seeliger

Blake Richards

Jenann Ismael

...

2023/7

Characterising representation dynamics in recurrent neural networks for object recognition

arXiv preprint arXiv:2308.12435

Sushrut Thorat

Adrien Doerig

Tim C Kietzmann

2023/8/23

Deep neural networks and visuo-semantic models explain complementary components of human ventral-stream representational dynamics

Journal of Neuroscience

Kamila M Jozwik

Tim C Kietzmann

Radoslaw M Cichy

Nikolaus Kriegeskorte

Marieke Mur

2023/3/8

What did you expect? Prediction error tuning in sensory cortex

David Richter

Tim C Kietzmann

Floris P de Lange

2023

Deep neural networks are not a single hypothesis but a language for expressing computational hypotheses

Behavioral and Brain Sciences

Tal Golan

JohnMark Taylor

Heiko Schütt

Benjamin Peters

Rowan P Sommers

...

2023/12/6

End-to-end topographic networks as models of cortical map formation and human visual behaviour: moving beyond convolutions

arXiv preprint arXiv:2308.09431

Zejin Lu

Adrien Doerig

Victoria Bosch

Bas Krahmer

Daniel Kaiser

...

2023/8/18

Empirically Identifying and Computationally Modeling the Brain–Behavior Relationship for Human Scene Categorization

Journal of Cognitive Neuroscience

Agnessa Karapetian

Antoniya Boyanova

Muthukumar Pandaram

Klaus Obermayer

Tim C Kietzmann

...

2023/11/1

The brain can’t copy-paste: End-to-end topographic neural networks as a way forward for modelling cortical map formation and behaviour

Zejin Lu

Adrien Doerig

Victoria Manglano Bosch

Bas Krahmer

Daniel Kaiser

...

2023

Neural representation of occluded objects in visual cortex

Journal of Vision

Courtney Mansfield

Tim Kietzmann

Jasper van den Bosch

Ian Charest

Marieke Mur

...

2023/8/1

From photos to sketches-how humans and deep neural networks process objects across different levels of visual abstraction

Journal of vision

Johannes JD Singer

Katja Seeliger

Tim C Kietzmann

Martin N Hebart

2022/2/1

Talk session 20. Computational Modelling Predictive coding is a consequence of energy efficiency in neural networks

Abdullahi Ali

Nasir Ahmad

Elgar de Groot

Marcel van Gerven

Tim Kietzmann

2022

Predictive coding is a consequence of energy efficiency in recurrent neural networks

Patterns

Abdullahi Ali

Nasir Ahmad

Elgar de Groot

Marcel Antonius Johannes van Gerven

Tim Christian Kietzmann

2022/12/9

Scene representations and categorization reaction times correlate in a time-window between 100 and 200 ms

Agnessa Karapetian

Antoniya Boyanova

Muthukumar Pandaram

Klaus Obermayer

Tim Kietzmann

...

2022

Visual and semantic factors in object recognition

Journal of Vision

Inga María Ólafsdóttir

Sunneva Líf Albertsdóttir

Unnur Andrea Ásgeirsdóttir

Tim C Kietzmann

Heida Maria Sigurdardottir

2022/12/5

See List of Professors in Tim C Kietzmann University(Radboud Universiteit)

Co-Authors

H-index: 80
Peter König

Peter König

Universität Osnabrück

H-index: 67
Nikolaus Kriegeskorte

Nikolaus Kriegeskorte

Columbia University in the City of New York

H-index: 46
Olaf Hauk

Olaf Hauk

University of Cambridge

H-index: 45
Jan Kietzmann

Jan Kietzmann

University of Victoria

H-index: 43
Frank Tong

Frank Tong

Vanderbilt University

H-index: 41
Ian McCarthy

Ian McCarthy

Simon Fraser University

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