Spatial–temporal recurrent reinforcement learning for autonomous ships. Neural Networks, (165):634-653, 2023. [PUMA: topic_engineering Autonomous COLREG Deep Recurrency, learning, reinforcement surface vehicle] URL
Federated Learning on Transcriptomic Data: Model Quality and Performance Trade-Offs. Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part IV, 279–293, Springer-Verlag, Berlin, Heidelberg, 2024. [PUMA: area_responsibleai topic_lifescience Cell Classification, Disease Federated Learning, Prognosis Type] URL
Chapter 5 - Artificial intelligence (AI) enhanced nanomotors and active matter. In Yuebing Zheng, and Zilong Wu (Eds.), Intelligent Nanotechnology, 113--144, Elsevier, 2023. [PUMA: topic_physchemistry Active Feedback Machine Multi Optical Reinforcement agent control control, learning, particles, reinforcement] URL
NDP-RANK: Prediction and ranking of NDP systems performance using machine learning. Microprocessors and Microsystems, (96):104707, 2023. [PUMA: topic_federatedlearn Design Machine Modeling, Near-data Prediction, exploration learning, processing, space] URL
Explaining the Unexplainable: The Impact of Misleading Explanations on Trust in Unreliable Predictions for Hardly Assessable Tasks. Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization, 36–46, Association for Computing Machinery, New York, NY, USA, 2024. [PUMA: topic_visualcomputing XAI, explainability, learning, machine trust] URL
ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets. Pattern Recognition, (147):110138, 2024. [PUMA: topic_lifescience Convex GAN, Imbalanced LoRAS, Tabular data data, learning, space] URL