Zobrazeno 1 - 10
of 4 460
pro vyhledávání: '"Lin, Ji"'
Publikováno v:
New J. Phys. 26, 093020 (2024)
We analytically and numerically study three-component rogue waves (RWs) in spin-1 Bose-Einstein condensates with Raman-induced spin-orbit coupling (SOC). Using the multiscale perturbative method, we obtain approximate analytical solutions for RWs wit
Externí odkaz:
http://arxiv.org/abs/2409.01613
Autor:
Lin, Ji
Deep learning has prevailed in various fields and fundamentally changed human society. Efficiency is the key factor in democratizing deep learning and broadening its applications. It is increasingly important as Moore’s law slows down while the mod
The US FDA's Project Optimus initiative that emphasizes dose optimization prior to marketing approval represents a pivotal shift in oncology drug development. It has a ripple effect for rethinking what changes may be made to conventional pivotal tria
Externí odkaz:
http://arxiv.org/abs/2406.00196
This paper discusses the construction of a new $(3+1)$-dimensional Korteweg-de Vries (KdV) equation. By employing the KdV's recursion operator, we extract two equations, and with elemental computation steps, the obtained result is $ 3u_{xyt}+3u_{xzt}
Externí odkaz:
http://arxiv.org/abs/2404.17156
Publikováno v:
IEEE Circuits and Systems Magazine, 23(3), pp. 8-34, October 2023
Tiny Machine Learning (TinyML) is a new frontier of machine learning. By squeezing deep learning models into billions of IoT devices and microcontrollers (MCUs), we expand the scope of AI applications and enable ubiquitous intelligence. However, Tiny
Externí odkaz:
http://arxiv.org/abs/2403.19076
Autor:
Lin, Ji, Yin, Hongxu, Ping, Wei, Lu, Yao, Molchanov, Pavlo, Tao, Andrew, Mao, Huizi, Kautz, Jan, Shoeybi, Mohammad, Han, Song
Visual language models (VLMs) rapidly progressed with the recent success of large language models. There have been growing efforts on visual instruction tuning to extend the LLM with visual inputs, but lacks an in-depth study of the visual language p
Externí odkaz:
http://arxiv.org/abs/2312.07533
Recent studies focus on embedding learning over knowledge graphs, which map entities and relations in knowledge graphs into low-dimensional vector spaces. While existing models mainly consider the aspect of graph structure, there exists a wealth of c
Externí odkaz:
http://arxiv.org/abs/2401.02968
Publikováno v:
56th IEEE/ACM International Symposium on Microarchitecture (MICRO 2023)
On-device learning and efficient fine-tuning enable continuous and privacy-preserving customization (e.g., locally fine-tuning large language models on personalized data). However, existing training frameworks are designed for cloud servers with powe
Externí odkaz:
http://arxiv.org/abs/2310.17752
Autor:
Javed, Faisal, Lin, Ji
Publikováno v:
Chinese Journal of Physics 88(2024)786-798
Gravastars, theoretical alternatives to black holes, have captured the interest of scientists in astrophysics due to their unique properties. This paper aims to further investigate the exact solution of a novel gravastar model based on the Mazur-Mott
Externí odkaz:
http://arxiv.org/abs/2309.17023
Publikováno v:
Phys. Rev. E 105, 014205 (2022)
In this paper, we study in detail the nonlinear propagation of magnetic soliton in a ferromagnetic film. The sample is magnetized to saturation by an external field perpendicular to film plane. A new generalized (2+1)-dimensional short-wave asymptoti
Externí odkaz:
http://arxiv.org/abs/2307.00903