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The Super-Turing Computational Power of Interactive Evolving Recurrent Neural Networks.

, and . ICANN, volume 8131 of Lecture Notes in Computer Science, page 58-65. Springer, (2013)

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Argument Mining with Modular BERT and Transfer Learning., and . IJCNN, page 1-8. IEEE, (2023)The EsnTorch Library: Efficient Implementation of Transformer-Based Echo State Networks., , , , and . ICONIP (7), volume 1794 of Communications in Computer and Information Science, page 235-246. Springer, (2022)The Wadge Hierarchy of Max-Regular Languages., , , and . FSTTCS, volume 4 of LIPIcs, page 121-132. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2009)Emulation of finite state automata with networks of synfire rings., and . IJCNN, page 4641-4648. IEEE, (2017)Computational capabilities of recurrent neural networks based on their attractor dynamics., and . IJCNN, page 1-8. IEEE, (2015)In-Context Learning and Fine-Tuning GPT for Argument Mining., , and . CoRR, (2024)Interactive Evolving Recurrent Neural Networks Are Super-turing.. ICAART (1), page 328-333. SciTePress, (2012)Automata complete computation with Hodgkin-Huxley neural networks composed of synfire rings., and . Neural Networks, (2020)Robust Optimal-Size Implementation of Finite State Automata with Synfire Ring-Based Neural Networks., and . ICANN (1), volume 11727 of Lecture Notes in Computer Science, page 806-818. Springer, (2019)Expressive Power of Non-deterministic Evolving Recurrent Neural Networks in Terms of Their Attractor Dynamics., and . UCNC, volume 9252 of Lecture Notes in Computer Science, page 144-156. Springer, (2015)