Publications (38)
Adaptive Gradient Learning for Spiking Neural Networks by Exploiting Membrane Potential Dynamics
Jiaqiang Jiang, Lei Wang, Runhao Jiang +2
Brain-inspired spiking neural networks (SNNs) are recognized as a promising avenue for achieving efficient, low-energy neuromorphic computing. Recent advancements have focused on d…
Unusually high phonon thermal conductivity in the Weyl semimetal TaP: A comparative study with TaAs
Xianyong Ding, Xin Jin, Dengfeng Li +5
In many metals, thermal transport is often dominated by electrons, although the lattice contribution can remain appreciable depending on the material. Here, through rigorous first-…
Electric and magnetic fields tuned spin-polarized topological phases in two-dimensional ferromagnetic MnBiTe
Shi Xiao, Xiaoliang Xiao, Fangyang Zhan +3
Applying electric or magnetic fields is widely used to not only create and manipulate topological states but also facilitate their observations in experiments. In this work, we sho…
Localized Traffic Sign Detection with Multi-scale Deconvolution Networks
Songwen Pei, Fuwu Tang, Yanfei Ji +2
Autonomous driving is becoming a future practical lifestyle greatly driven by deep learning. Specifically, an effective traffic sign detection by deep learning plays a critical rol…
Intrinsic quantum anomalous Hall phase induced by proximity in germanene/CrGeTe van der Waals heterostructure
Ruiling Zou, Fangyang Zhan, Baobing Zheng +3
A van der Waals heterostructure combined with intrinsic magnetism and topological orders have recently paved attractive avenues to realize quantum anomalous Hall effects. In this w…
Single pair of charge-two high-fold fermions with type-II van Hove singularities on the surface of ultralight chiral crystals
Xiaoliang Xiao, Yuanjun Jin, Da-Shuai Ma +4
The realization of single-pair chiral fermions in Weyl systems remains challenging in topology physics, especially for the systems with higher chiral charges . In this work, bas…