31 citations · 91 across the 9 of their papers we have counts for
10 papers
Darkit: A User-Friendly Software Toolkit for Spiking Large Language Model
Xin Du, Shifan Ye, Qian Zheng +7
Large language models (LLMs) have been widely applied in various practical applications, typically comprising billions of parameters, with inference processes requiring substantial…
GRSN: Gated Recurrent Spiking Neurons for POMDPs and MARL
Lang Qin, Ziming Wang, Runhao Jiang +2
Spiking neural networks (SNNs) are widely applied in various fields due to their energy-efficient and fast-inference capabilities. Applying SNNs to reinforcement learning (RL) can…
Neuromorphic Auditory Perception by Neural Spiketrum
Huajin Tang, Pengjie Gu, Jayawan Wijekoon +4
Neuromorphic computing holds the promise to achieve the energy efficiency and robust learning performance of biological neural systems. To realize the promised brain-like intellige…
Point-Based Value Iteration for POMDPs with Neural Perception Mechanisms
Rui Yan, Gabriel Santos, Gethin Norman +2
The increasing trend to integrate neural networks and conventional software components in safety-critical settings calls for methodologies for their formal modelling, verification…
Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes
Gehua Ma, Runhao Jiang, Rui Yan +1
Developing computational models of neural response is crucial for understanding sensory processing and neural computations. Current state-of-the-art neural network methods use temp…
Exploiting Noise as a Resource for Computation and Learning in Spiking Neural Networks
Gehua Ma, Rui Yan, Huajin Tang
https://cell.com/patterns/fulltext/S2666-3899(23)00200-3 Networks of spiking neurons underpin the extraordinary information-processing capabi…
A Low Latency Adaptive Coding Spiking Framework for Deep Reinforcement Learning
Lang Qin, Rui Yan, Huajin Tang
In recent years, spiking neural networks (SNNs) have been used in reinforcement learning (RL) due to their low power consumption and event-driven features. However, spiking reinfor…
Towards Lossless ANN-SNN Conversion under Ultra-Low Latency with Dual-Phase Optimization
Ziming Wang, Shuang Lian, Yuhao Zhang +3
Spiking neural networks (SNNs) operating with asynchronous discrete events show higher energy efficiency with sparse computation. A popular approach for implementing deep SNNs is A…
Automatic Subspace Learning via Principal Coefficients Embedding
Xi Peng, Jiwen Lu, Zhang Yi +1
In this paper, we address two challenging problems in unsupervised subspace learning: 1) how to automatically identify the feature dimension of the learned subspace (i.e., automati…
Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification
Xi Peng, Rui Yan, Bo Zhao +2
Spatial Pyramid Matching (SPM) and its variants have achieved a lot of success in image classification. The main difference among them is their encoding schemes. For example, ScSPM…