224 citations · 533 across the 21 of their papers we have counts for
7 papers · 1 filter
Spike timing reshapes robustness against attacks in spiking neural networks
Jianhao Ding, Zhaofei Yu, Tiejun Huang +1
The success of deep learning in the past decade is partially shrouded in the shadow of adversarial attacks. In contrast, the brain is far more robust at complex cognitive tasks. Ut…
Towards the Next Generation of Retinal Neuroprosthesis: Visual Computation with Spikes
Zhaofei Yu, Jian K. Liu, Shanshan Jia +4
Neuroprosthesis, as one type of precision medicine device, is aiming for manipulating neuronal signals of the brain in a closed-loop fashion, together with receiving stimulus from…
Reconstruction of Natural Visual Scenes from Neural Spikes with Deep Neural Networks
Yichen Zhang, Shanshan Jia, Yajing Zheng +5
Neural coding is one of the central questions in systems neuroscience for understanding how the brain processes stimulus from the environment, moreover, it is also a cornerstone fo…
Probabilistic Inference of Binary Markov Random Fields in Spiking Neural Networks through Mean-field Approximation
Yajing Zheng, Shanshan Jia, Zhaofei Yu +3
Recent studies have suggested that the cognitive process of the human brain is realized as probabilistic inference and can be further modeled by probabilistic graphical models like…
Revealing Fine Structures of the Retinal Receptive Field by Deep Learning Networks
Qi Yan, Yajing Zheng, Shanshan Jia +6
Deep convolutional neural networks (CNNs) have demonstrated impressive performance on many visual tasks. Recently, they became useful models for the visual system in neuroscience.…
Winner-Take-All as Basic Probabilistic Inference Unit of Neuronal Circuits
Zhaofei Yu, Yonghong Tian, Tiejun Huang +1
Experimental observations of neuroscience suggest that the brain is working a probabilistic way when computing information with uncertainty. This processing could be modeled as Bay…