Zobrazeno 1 - 10
of 21 273
pro vyhledávání: '"ZHANG, Ya"'
Medical image segmentation has recently demonstrated impressive progress with deep neural networks, yet the heterogeneous modalities and scarcity of mask annotations limit the development of segmentation models on unannotated modalities. This paper i
Externí odkaz:
http://arxiv.org/abs/2412.04106
As a globally celebrated sport, soccer has attracted widespread interest from fans all over the world. This paper aims to develop a comprehensive multi-modal framework for soccer video understanding. Specifically, we make the following contributions
Externí odkaz:
http://arxiv.org/abs/2412.01820
We revisit the challenging problem of identifying the quantum spin liquid candidate in the spin-1/2 $J_1$-$J_2$ Heisenberg antiferromagnet on the square lattice. By integrating the Gutzwiller-guided density matrix renormalization group method with an
Externí odkaz:
http://arxiv.org/abs/2411.14114
Training a generalizable agent to continually learn a sequence of tasks from offline trajectories is a natural requirement for long-lived agents, yet remains a significant challenge for current offline reinforcement learning (RL) algorithms. Specific
Externí odkaz:
http://arxiv.org/abs/2411.11364
Autor:
Wang, Pingjie, Zhao, Zihan, Zhao, Liudan, He, Miao, Sun, Xin, Zhang, Ya, Sun, Kun, Wang, Yanfeng, Wang, Yu
Auscultation of internal body sounds is essential for diagnosing a range of health conditions, yet its effectiveness is often limited by clinicians' expertise and the acoustic constraints of human hearing, restricting its use across various clinical
Externí odkaz:
http://arxiv.org/abs/2411.07547
In this work, we demonstrate a kinetic superconductor in a simple lattice model with only one term: the nearest neighbor hopping $t$. The hopping is projected into a constrained Hilbert space, in the same spirit as the usual t-J model with $J=0$, whe
Externí odkaz:
http://arxiv.org/abs/2411.07292
Autor:
Zhou, Boran, Zhang, Ya-Hui
The recent experimental observation of quantum anomalous Hall (QAH) effects in the rhombohedrally stacked pentalayer graphene has motivated theoretical discussions on the possibility of quantum anomalous Hall crystal (QAHC), a topological version of
Externí odkaz:
http://arxiv.org/abs/2411.04174
Autor:
Yang, Hui, Zhang, Ya-Hui
We performed a random phase approximation (RPA) calculation for a spin-valley polarized model of the rhombohedral tetra-layer graphene to study the possibility of chiral superconductor from the Kohn-Luttinger mechanism. We included the realistic band
Externí odkaz:
http://arxiv.org/abs/2411.02503
Offline reinforcement learning (RL) methods harness previous experiences to derive an optimal policy, forming the foundation for pre-trained large-scale models (PLMs). When encountering tasks not seen before, PLMs often utilize several expert traject
Externí odkaz:
http://arxiv.org/abs/2411.01168
The purpose of offline multi-task reinforcement learning (MTRL) is to develop a unified policy applicable to diverse tasks without the need for online environmental interaction. Recent advancements approach this through sequence modeling, leveraging
Externí odkaz:
http://arxiv.org/abs/2411.01146