Cornelius Weber

2.6k total citations
93 papers, 1.4k citations indexed

About

Cornelius Weber is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Cornelius Weber has authored 93 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Artificial Intelligence, 37 papers in Computer Vision and Pattern Recognition and 25 papers in Cognitive Neuroscience. Recurrent topics in Cornelius Weber's work include Reinforcement Learning in Robotics (18 papers), Neural dynamics and brain function (17 papers) and Robot Manipulation and Learning (14 papers). Cornelius Weber is often cited by papers focused on Reinforcement Learning in Robotics (18 papers), Neural dynamics and brain function (17 papers) and Robot Manipulation and Learning (14 papers). Cornelius Weber collaborates with scholars based in Germany, United Kingdom and China. Cornelius Weber's co-authors include Stefan Wermter, Pablo Barros, German I. Parisi, Sven Magg, Jochen Triesch, Jun Tani, Nicolás Navarro-Guerrero, Francisco Cruz, Mark Elshaw and Doreen Jirak and has published in prestigious journals such as SHILAP Revista de lepidopterología, Philosophical Transactions of the Royal Society B Biological Sciences and PLoS Computational Biology.

In The Last Decade

Cornelius Weber

86 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Cornelius Weber Germany 19 584 457 248 217 204 93 1.4k
Jim Tørresen Norway 26 739 1.3× 700 1.5× 249 1.0× 155 0.7× 197 1.0× 211 2.7k
Antonio Chella Italy 23 645 1.1× 289 0.6× 378 1.5× 243 1.1× 275 1.3× 169 1.5k
Kwee-Bo Sim South Korea 16 406 0.7× 362 0.8× 354 1.4× 150 0.7× 55 0.3× 178 1.4k
Mohammed Yeasin United States 21 406 0.7× 612 1.3× 485 2.0× 91 0.4× 103 0.5× 107 1.8k
Andrea Bonarini Italy 22 612 1.0× 356 0.8× 172 0.7× 338 1.6× 149 0.7× 140 1.5k
Pablo Barros Germany 18 247 0.4× 506 1.1× 138 0.6× 78 0.4× 161 0.8× 58 1.0k
Bradley J. Rhodes United States 17 517 0.9× 618 1.4× 266 1.1× 93 0.4× 141 0.7× 50 1.8k
Hongan Wang China 25 432 0.7× 837 1.8× 469 1.9× 199 0.9× 97 0.5× 203 2.4k
Nicola Bellotto United Kingdom 21 295 0.5× 837 1.8× 120 0.5× 203 0.9× 183 0.9× 70 1.5k
Marc Cavazza United Kingdom 24 1.0k 1.8× 634 1.4× 335 1.4× 430 2.0× 251 1.2× 181 2.3k

Countries citing papers authored by Cornelius Weber

Since Specialization
Citations

This map shows the geographic impact of Cornelius Weber's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cornelius Weber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cornelius Weber more than expected).

Fields of papers citing papers by Cornelius Weber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cornelius Weber. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cornelius Weber. The network helps show where Cornelius Weber may publish in the future.

Co-authorship network of co-authors of Cornelius Weber

This figure shows the co-authorship network connecting the top 25 collaborators of Cornelius Weber. A scholar is included among the top collaborators of Cornelius Weber based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Cornelius Weber. Cornelius Weber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Weber, Cornelius, et al.. (2024). QT-TDM: Planning With Transformer Dynamics Model and Autoregressive Q-Learning. IEEE Robotics and Automation Letters. 10(1). 112–119. 1 indexed citations
2.
Li, Taihao, et al.. (2023). Disentangling Prosody Representations With Unsupervised Speech Reconstruction. IEEE/ACM Transactions on Audio Speech and Language Processing. 32. 39–54. 4 indexed citations
3.
Yao, Yuan, Tianyu Yu, Ao Zhang, et al.. (2023). Visually Grounded Commonsense Knowledge Acquisition. Proceedings of the AAAI Conference on Artificial Intelligence. 37(5). 6583–6592. 2 indexed citations
4.
Kerzel, Matthias, et al.. (2022). Language-Model-Based Paired Variational Autoencoders for Robotic Language Learning. IEEE Transactions on Cognitive and Developmental Systems. 15(4). 1812–1824. 3 indexed citations
5.
Weber, Cornelius, et al.. (2022). LipSound2: Self-Supervised Pre-Training for Lip-to-Speech Reconstruction and Lip Reading. IEEE Transactions on Neural Networks and Learning Systems. 35(2). 2772–2782. 17 indexed citations
6.
Weber, Cornelius, et al.. (2020). Improving robot dual-system motor learning with intrinsically motivated meta-control and latent-space experience imagination. Robotics and Autonomous Systems. 133. 103630–103630. 11 indexed citations
7.
Fu, Di, Cornelius Weber, Guochun Yang, et al.. (2019). What can computational models learn from human selective attention? A review from an audiovisual unimodal and crossmodal perspective. PsyArXiv (OSF Preprints). 1 indexed citations
8.
Fu, Di, Cornelius Weber, Matthias Kerzel, et al.. (2019). What can computational models learn from human selective attention? A review from an audiovisual crossmodal perspective. PsyArXiv (OSF Preprints). 1 indexed citations
9.
Mao, Jiayuan, Yuan Yao, Stefan Heinrich, et al.. (2019). Bootstrapping Knowledge Graphs From Images and Text. Frontiers in Neurorobotics. 13. 93–93. 4 indexed citations
10.
Kerzel, Matthias, et al.. (2018). Slowness-based neural visuomotor control with an Intrinsically motivated Continuous Actor-Critic.. ePrints Soton (University of Southampton). 1 indexed citations
11.
Weber, Cornelius, et al.. (2018). Image-to-Text Transduction with Spatial Self-Attention.. The European Symposium on Artificial Neural Networks. 1 indexed citations
12.
Weber, Cornelius, et al.. (2017). Reusing Neural Speech Representations for Auditory Emotion Recognition. International Joint Conference on Natural Language Processing. 1. 423–430. 10 indexed citations
13.
Parisi, German I., Jun Tani, Cornelius Weber, & Stefan Wermter. (2017). Lifelong learning of human actions with deep neural network self-organization. Neural Networks. 96. 137–149. 79 indexed citations
14.
Heinrich, Stefan, Cornelius Weber, Stefan Wermter, et al.. (2016). Crossmodal Language Grounding, Learning, and Teaching.. Neural Information Processing Systems. 3 indexed citations
15.
Parisi, German I., Cornelius Weber, & Stefan Wermter. (2015). Self-organizing neural integration of pose-motion features for human action recognition. Frontiers in Neurorobotics. 9. 3–3. 55 indexed citations
16.
Barros, Pablo, Doreen Jirak, Cornelius Weber, & Stefan Wermter. (2015). Multimodal emotional state recognition using sequence-dependent deep hierarchical features. Neural Networks. 72. 140–151. 58 indexed citations
17.
Weber, Cornelius, et al.. (2013). Learning indoor robot navigation using visual and sensorimotor map information. Frontiers in Neurorobotics. 7. 15–15. 7 indexed citations
18.
Saeb, Sohrab, Cornelius Weber, & Jochen Triesch. (2011). Learning the Optimal Control of Coordinated Eye and Head Movements. PLoS Computational Biology. 7(11). e1002253–e1002253. 24 indexed citations
19.
20.
Weber, Cornelius, Helge Ritter, Jack D. Cowan, & Klaus Obermayer. (1997). Development and regeneration of the retinotectal map in goldfish: a computational study. Philosophical Transactions of the Royal Society B Biological Sciences. 352(1361). 1603–1623. 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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