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pro vyhledávání: '"Lim BY"'
Autor:
Lim, Soon Wei Daniel, Kee, Yong How, Smith, Scott Nicholas Allan, Tan, Shan Mei, Lim, An Eng, Yang, Yuansheng, Goh, Shireen
Inertial microfluidics has been limited to dilute particle concentrations due to defocusing (spreading out) at high particle concentrations. We observe a counterintuitive shift of focusing to the outer curved wall under high concentration flow, which
Externí odkaz:
http://arxiv.org/abs/2409.12488
Autor:
Lim, Ik Soo, Masuda, Naoki
Trust and reciprocation of it form the foundation of economic, social and other interactions. While the Trust Game is widely used to study these concepts for interactions between two players, often alternating different roles (i.e., investor and trus
Externí odkaz:
http://arxiv.org/abs/2411.14845
We introduce an Implicit Game-Theoretic MPC (IGT-MPC), a decentralized algorithm for two-agent motion planning that uses a learned value function that predicts the game-theoretic interaction outcomes as the terminal cost-to-go function in a model pre
Externí odkaz:
http://arxiv.org/abs/2411.13983
Autor:
Lim, Wee Han, Tanttu, Tuomo, Youn, Tony, Huang, Jonathan Yue, Serrano, Santiago, Dickie, Alexandra, Yianni, Steve, Hudson, Fay E., Escott, Christopher C., Yang, Chih Hwan, Laucht, Arne, Saraiva, Andre, Chan, Kok Wai, Cifuentes, Jesús D., Dzurak, Andrew S.
Recent advances in semiconductor spin qubits have achieved linear arrays exceeding ten qubits. Moving to two-dimensional (2D) qubit arrays is a critical next step to advance towards fault-tolerant implementations, but it poses substantial fabrication
Externí odkaz:
http://arxiv.org/abs/2411.13882
An onboard prediction of dynamic parameters (e.g. Aerodynamic drag, rolling resistance) enables accurate path planning for EVs. This paper presents EV-PINN, a Physics-Informed Neural Network approach in predicting instantaneous battery power and cumu
Externí odkaz:
http://arxiv.org/abs/2411.14691
Entanglement fluctuations associated with Schr\"{o}dinger evolution of wavefunctions offer a unique perspective on various fundamental issues ranging from quantum thermalization to state preparation in quantum devices. Very recently, a subset of pres
Externí odkaz:
http://arxiv.org/abs/2411.14687
Generating large-scale, domain-specific, multilingual multi-turn dialogue datasets remains a significant hurdle for training effective Multi-Turn Intent Classification models in chatbot systems. In this paper, we introduce Chain-of-Intent, a novel me
Externí odkaz:
http://arxiv.org/abs/2411.14252
LLM-based autonomous agents have demonstrated outstanding performance in solving complex industrial tasks. However, in the pursuit of carbon neutrality and high-performance renewable energy systems, existing AI-assisted design automation faces signif
Externí odkaz:
http://arxiv.org/abs/2411.14214
Autor:
Zhang, Gong, Primaatmaja, Ignatius William, Chen, Yue, Ng, Si Qi, Ng, Hong Jie, Pistoia, Marco, Gong, Xiao, Goh, Koon Tong, Wang, Chao, Lim, Charles
The power of quantum random number generation is more than just the ability to create truly random numbers$\unicode{x2013}$it can also enable self-testing, which allows the user to verify the implementation integrity of certain critical quantum compo
Externí odkaz:
http://arxiv.org/abs/2411.13712
Autor:
Jin, Yuhao, Gao, Qizhong, Zhu, Xiaohui, Yue, Yong, Lim, Eng Gee, Chen, Yuqing, Wong, Prudence, Chu, Yijie
While deep learning-based robotic grasping technology has demonstrated strong adaptability, its computational complexity has also significantly increased, making it unsuitable for scenarios with high real-time requirements. Therefore, we propose a lo
Externí odkaz:
http://arxiv.org/abs/2411.12520