Zobrazeno 1 - 10
of 3 045
pro vyhledávání: '"Nguyen P. Anh"'
Autor:
Nguyen, Viet Anh, Nguyen, Linh Thi Dieu, Do, Thi Thu Ha, Wu, Ye, Sergeev, Aleksandr A., Zhu, Ding, Valuckas, Vytautas, Pham, Duong, Bui, Hai Xuan Son, Hoang, Duy Mai, Bui, Son Tung, Bui, Xuan Khuyen, Nguyen, Binh Thanh, Nguyen, Hai Son, Vu, Lam Dinh, Rogach, Andrey, Ha, Son Tung, Le-Van, Quynh
Publikováno v:
J Phys Chem Lett J Phys Chem Lett . 2024 Nov 14;15(45):11291-11299
Enhancing light emission from perovskite nanocrystal (NC) films is essential in light-emitting devices, as their conventional stacks often restrict the escape of emitted light. This work addresses this challenge by employing a TiO$_2$ grating to enha
Externí odkaz:
http://arxiv.org/abs/2411.12463
Latent space optimization (LSO) is a powerful method for designing discrete, high-dimensional biological sequences that maximize expensive black-box functions, such as wet lab experiments. This is accomplished by learning a latent space from availabl
Externí odkaz:
http://arxiv.org/abs/2411.11265
Autor:
Nguyen, Le-Anh, Bui, Minh-Loc
Background: Beta-delayed proton emission from neutron halo nuclei $^{11}$Be represents a rare decay process. The existence of the narrow resonance near the proton-emission threshold in $^{11}$B explains its unexpectedly high probability. However, the
Externí odkaz:
http://arxiv.org/abs/2411.10700
Autor:
Silva, Allyson, Scherer, Artur, Webb, Zak, Khalid, Abdullah, Kulchytskyy, Bohdan, Kramer, Mia, Nguyen, Kevin, Kong, Xiangzhou, Dagnew, Gebremedhin A., Wang, Yumeng, Nguyen, Huy Anh, Olfert, Katiemarie, Ronagh, Pooya
We propose a novel technique for optimizing a modular fault-tolerant quantum computing architecture, taking into account any desired space-time trade--offs between the number of physical qubits and the fault-tolerant execution time of a quantum algor
Externí odkaz:
http://arxiv.org/abs/2411.04270
Fairness in artificial intelligence and machine learning (AI/ML) models is becoming critically important, especially as decisions made by these systems impact diverse groups. In education, a vital sector for all countries, the widespread application
Externí odkaz:
http://arxiv.org/abs/2410.06423
Autor:
Nguyen, Quang Anh, Tomeh, Nadi, Lebbah, Mustapha, Charnois, Thierry, Azzag, Hanene, Muñoz, Santiago Cordoba
With the continuous development of pre-trained language models, prompt-based training becomes a well-adopted paradigm that drastically improves the exploitation of models for many natural language processing tasks. Prompting also shows great performa
Externí odkaz:
http://arxiv.org/abs/2410.06173
Autor:
Nguyen, Tuan Anh
We prove that multilevel Picard approximations are capable of approximating solutions of semilinear heat equations in $L^{p}$-sense, ${p}\in [2,\infty)$, in the case of gradient-dependent, Lipschitz-continuous nonlinearities, in the sense that the co
Externí odkaz:
http://arxiv.org/abs/2410.00203
Autor:
Neufeld, Ariel, Nguyen, Tuan Anh
We prove that multilevel Picard approximations and deep neural networks with ReLU, leaky ReLU, and softplus activation are capable of approximating solutions of semilinear Kolmogorov PDEs in $L^\mathfrak{p}$-sense, $\mathfrak{p}\in [2,\infty)$, in th
Externí odkaz:
http://arxiv.org/abs/2409.20431
Autor:
Pham, Duy-Tung, Vu, Thien Trang Nguyen, Nguyen, Tung, Van, Linh Ngo, Nguyen, Duc Anh, Nguyen, Thien Huu
Recent advances in neural topic models have concentrated on two primary directions: the integration of the inference network (encoder) with a pre-trained language model (PLM) and the modeling of the relationship between words and topics in the genera
Externí odkaz:
http://arxiv.org/abs/2409.19749
Unsupervised pre-training on vast amounts of graph data is critical in real-world applications wherein labeled data is limited, such as molecule properties prediction or materials science. Existing approaches pre-train models for specific graph domai
Externí odkaz:
http://arxiv.org/abs/2409.19117