Thomas Lukasiewicz
Professor Thomas Lukasiewicz
Themes:
- Artificial Intelligence and Machine Learning
- Data, Knowledge and Action
- Algorithms and Complexity Theory
Completed Projects:
Interests
For more information on Thomas Lukasiewicz and his team, see: Intelligent Systems Lab.
Selected Publications
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Hybrid Reinforced Medical Report Generation with M−Linear Attention and Repetition Penalty
Zhenghua Xu‚ Wenting Xu‚ Ruizhi Wang‚ Junyang Chen‚ Chang Qi and Thomas Lukasiewicz
In IEEE Transactions on Neural Networks and Learning Systems. Vol. 36. No. 2. Pages 2206–2220. February, 2025.
Details about Hybrid Reinforced Medical Report Generation with M−Linear Attention and Repetition Penalty | BibTeX data for Hybrid Reinforced Medical Report Generation with M−Linear Attention and Repetition Penalty | DOI (https://doi.org/10.1109/TNNLS.2023.3343391)
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Aggregated Mutual Learning between CNN and Transformer for semi−supervised medical image segmentation
Zhenghua Xu‚ Hening Wang‚ Runhe Yang‚ Yuchen Yang‚ Weipeng Liu and Thomas Lukasiewicz
In Knowledge−Based Systems. Vol. 311. Pages 113005. 2025.
Details about Aggregated Mutual Learning between CNN and Transformer for semi−supervised medical image segmentation | BibTeX data for Aggregated Mutual Learning between CNN and Transformer for semi−supervised medical image segmentation | DOI (https://doi.org/10.1016/j.knosys.2025.113005) | Link to Aggregated Mutual Learning between CNN and Transformer for semi−supervised medical image segmentation
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Benchmarking Predictive Coding Networks – Made Simple
Luca Pinchetti‚ Chang Qi‚ Oleh Lokshyn‚ Cornelius Emde‚ Amine M'Charrak‚ Mufeng Tang‚ Simon Frieder‚ Bayar Menzat‚ Gaspard Oliviers‚ Rafal Bogacz‚ Thomas Lukasiewicz and Tommaso Salvatori
In Proceedings of the 13th International Conference on Learning Representations‚ ICLR 2025‚ Singapore‚ 24–28 April 2025. 2025.
Details about Benchmarking Predictive Coding Networks – Made Simple | BibTeX data for Benchmarking Predictive Coding Networks – Made Simple