Control and regulation of skyrmionic topological charge in a novel synthetic antiferromagnetic nanostructure

Abstract

Skyrmionium is a combination of a skyrmion with a topological charge (Q is +1 or −1), resulting in a magnetic configuration with a total topological charge of Q = 0....

SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence

“…The increasing number of adoptions by the community is symbolic of the success of a framework. Since being open-sourced in December 2019, SpikingJelly has been widely used in many spiking deep learning studies, including adversarial attack ( 100 , 101 ), ANN2SNN ( 95 , 102 – 106 ), attention mechanisms ( 107 , 108 ), depth estimation from DVS data ( 69 , 109 ), development of innovative materials ( 110 ), emotion recognition ( 111 ), energy estimation ( 112 ), event-based video reconstruction ( 113 ), fault diagnosis ( 114 ), hardware design ( 115 – 117 ), network structure improvements ( 60 , 61 , 118 – 121 ), spiking neuron improvements ( 56 , 122 – 127 ), training method improvements ( 128 – 138 ), medical diagnosis ( 139 , 140 ), network pruning ( 141 – 145 ), neural architecture search ( 146 , 147 ), neuromorphic data augmentation ( 148 ), natural language processing ( 149 ), object detection/tracking for DVS/frame data ( 65 , 66 , 150 ), odor recognition ( 151 ), optical flow estimation with DVS data ( 152 ), reinforcement learning for controlling ( 153 – 155 ), and semantic communication ( 156 ). Figure 1F shows parts of these adoptions.…”

“…The increasing number of adoptions by the community is symbolic of the success of a framework. Since being open-sourced in December 2019, SpikingJelly has been widely used in many spiking deep learning studies, including adversarial attack (100, 101), ANN2SNN (95,(102)(103)(104)(105)(106), attention mechanisms (107,108), depth estimation from DVS data (69,109), development of innovative materials (110), emotion recognition (111), energy estimation (112), eventbased video reconstruction (113), fault diagnosis (114), hardware design (115)(116)(117), network structure improvements (60,61,(118)(119)(120)(121), spiking neuron improvements (56,(122)(123)(124)(125)(126)(127), training method improvements (128)(129)(130)(131)(132)(133)(134)(135)(136)(137)(138), medical diagnosis (139,140), network pruning …”