Zobrazeno 1 - 10
of 1 119
pro vyhledávání: '"Chang, Yu‐Cheng"'
Autor:
Upadhyay, Rishabh, Karimi, Bayan, Subero, Diego, Satrya, Christoforus Dimas, Peltonen, Joonas T., Chang, Yu-Cheng, Pekola, Jukka P.
Thermodynamics in quantum circuits aims to find improved functionalities of thermal machines, highlight fundamental phenomena peculiar to quantum nature in thermodynamics, and point out limitations in quantum information processing due to coupling of
Externí odkaz:
http://arxiv.org/abs/2411.10774
Fuzzy Neural Networks (FNNs) are effective machine learning models for classification tasks, commonly based on the Takagi-Sugeno-Kang (TSK) fuzzy system. However, when faced with high-dimensional data, especially with noise, FNNs encounter challenges
Externí odkaz:
http://arxiv.org/abs/2410.13390
The rapid evolution of Brain-Computer Interfaces (BCIs) has significantly influenced the domain of human-computer interaction, with Steady-State Visual Evoked Potentials (SSVEP) emerging as a notably robust paradigm. This study explores advanced clas
Externí odkaz:
http://arxiv.org/abs/2410.12267
The paper introduces a Fuzzy-based Attention (Fuzzy Attention Layer) mechanism, a novel computational approach to enhance the interpretability and efficacy of neural models in psychological research. The proposed Fuzzy Attention Layer mechanism is in
Externí odkaz:
http://arxiv.org/abs/2409.17661
Autor:
Satrya, Christoforus Dimas, Chang, Yu-Cheng, Upadhyay, Rishabh, Makinen, Ilari K., Peltonen, Joonas T., Karimi, Bayan, Pekola, Jukka P.
Superconducting circuits provide a versatile and controllable platform for studies of fundamental quantum phenomena as well as for quantum technology applications. A conventional technique to read out the state of a quantum circuit or to characterize
Externí odkaz:
http://arxiv.org/abs/2409.13417
This paper presents a pioneering exploration into the integration of fine-grained human supervision within the autonomous driving domain to enhance system performance. The current advances in End-to-End autonomous driving normally are data-driven and
Externí odkaz:
http://arxiv.org/abs/2408.10908
Driving under drowsy conditions significantly escalates the risk of vehicular accidents. Although recent efforts have focused on using electroencephalography to detect drowsiness, helping prevent accidents caused by driving in such states, seamless h
Externí odkaz:
http://arxiv.org/abs/2408.07083
Autor:
Zhou, Jinzhao, Duan, Yiqun, Zhao, Ziyi, Chang, Yu-Cheng, Wang, Yu-Kai, Do, Thomas, Lin, Chin-Teng
Decoding linguistic information from non-invasive brain signals using EEG has gained increasing research attention due to its vast applicational potential. Recently, a number of works have adopted a generative-based framework to decode electroencepha
Externí odkaz:
http://arxiv.org/abs/2408.04679
Ensembling multiple models has always been an effective approach to push the limits of existing performance and is widely used in classification tasks by simply averaging the classification probability vectors from multiple classifiers to achieve bet
Externí odkaz:
http://arxiv.org/abs/2406.12585
Multi-agent systems often require agents to collaborate with or compete against other agents with diverse goals, behaviors, or strategies. Agent modeling is essential when designing adaptive policies for intelligent machine agents in multiagent syste
Externí odkaz:
http://arxiv.org/abs/2401.00132