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Neural Computation|September 22, 2025
Boosting MCTS With Free Energy MinimizationMawaba Pascal Dao, Adrian M PeterNeural Computation|February 16, 2024
Quantifying and Maximizing the Information Flux in Recurrent Neural NetworksClaus Metzner, Marius E Yamakou, Dennis Voelkl, et al.Neural Computation|March 8, 2024
Learning Korobov Functions by Correntropy and Convolutional Neural NetworksZhiying Fang, Tong Mao, Jun FanNeural Computation|March 8, 2024
Mathematical Modeling of PI3K/Akt Pathway in MicrogliaAlireza Poshtkohi, John Wade, Liam McDaid, et al.Neural Computation|March 8, 2024
Instance-Specific Model Perturbation Improves Generalized Zero-Shot LearningGuanyu Yang, Kaizhu Huang, Rui Zhang, et al.Neural Computation|March 8, 2024
An Overview of the Free Energy Principle and Related ResearchZhengquan Zhang, Feng XuNeural Computation|July 19, 2024
Trade-Offs Between Energy and Depth of Neural NetworksKei Uchizawa, Haruki AbeNeural Computation|August 23, 2024
Active Inference and Reinforcement Learning: A Unified Inference on Continuous State and Action Spaces Under Partial ObservabilityParvin Malekzadeh, Konstantinos N PlataniotisNeural Computation|September 23, 2024
KLIF: An Optimized Spiking Neuron Unit for Tuning Surrogate Gradient FunctionChunming Jiang, Yilei ZhangNeural Computation|October 9, 2024
Relating Human Error-Based Learning to Modern Deep RL AlgorithmsMichele Garibbo, Casimir J H Ludwig, Nathan F Lepora, et al.Pageof 301