7 citations · 11 across the 6 of their papers we have counts for
5 papers · 1 filter
Distillation-Guided Structural Transfer for Continual Learning Beyond Sparse Distributed Memory
Huiyan Xue, Xuming Ran, Yaxin Li +4
Sparse neural systems are gaining traction for efficient continual learning due to their modularity and low interference. Architectures such as Sparse Distributed Memory Multi-Laye…
Efficient ANN-SNN Conversion with Error Compensation Learning
Chang Liu, Jiangrong Shen, Xuming Ran +4
Artificial neural networks (ANNs) have demonstrated outstanding performance in numerous tasks, but deployment in resource-constrained environments remains a challenge due to their…
Brain-inspired continual pre-trained learner via silent synaptic consolidation
Xuming Ran, Juntao Yao, Yusong Wang +2
Pre-trained models have demonstrated impressive generalization capabilities, yet they remain vulnerable to catastrophic forgetting when incrementally trained on new tasks. Existing…
Machine Learning Applications on Neuroimaging for Diagnosis and Prognosis of Epilepsy: A Review
Jie Yuan, Xuming Ran, Keyin Liu +4
Machine learning is playing an increasingly important role in medical image analysis, spawning new advances in the clinical application of neuroimaging. There have been some review…
Bigeminal Priors Variational auto-encoder
Xuming Ran, Mingkun Xu, Qi Xu +2
Variational auto-encoders (VAEs) are an influential and generally-used class of likelihood-based generative models in unsupervised learning. The likelihood-based generative models…