17 citations · 21 across the 10 of their papers we have counts for
11 papers
SpikeCredit: Temporal Credit Carrier for Reinforcement Learning with Sparse Rewards
Yingchao Yu, Pengfei Sun, Wenxuan Pan +4
Reinforcement learning (RL) with sparse rewards is challenging because delayed outcomes provide little guidance about which intermediate computations caused success or failure. We…
Self-motion as a structural prior for coherent and robust formation of cognitive maps
Yingchao Yu, Pengfei Sun, Yaochu Jin +7
Most computational accounts of cognitive maps assume that stability is achieved primarily through sensory anchoring, with self-motion contributing to incremental positional updates…
Batch Normalization-Free Fully Integer Quantized Neural Networks via Progressive Tandem Learning
Pengfei Sun, Wenyu Jiang, Piew Yoong Chee +2
Quantised neural networks (QNNs) shrink models and reduce inference energy through low-bit arithmetic, yet most still depend on a running statistics batch normalisation (BN) layer,…
Algorithm-hardware co-design of neuromorphic networks with dual memory pathways
Pengfei Sun, Zhe Su, Jascha Achterberg +3
Spiking neural networks excel at event-driven sensing. Yet, maintaining task-relevant context over long timescales both algorithmically and in hardware, while respecting both tight…
Parallel Delayed Memory Units for Enhanced Temporal Modeling in Biomedical and Bioacoustic Signal Analysis
Pengfei Sun, Wenyu Jiang, Paul Devos +1
Advanced deep learning architectures, particularly recurrent neural networks (RNNs), have been widely applied in audio, bioacoustic, and biomedical signal analysis, especially in d…
Exploiting heterogeneous delays for efficient computation in low-bit neural networks
Pengfei Sun, Jascha Achterberg, Zhe Su +2
Neural networks rely on learning synaptic weights. However, this overlooks other neural parameters that can also be learned and may be utilized by the brain. One such parameter is…
EEG decoding with conditional identification information
Pengfei Sun, Jorg De Winne, Paul Devos +1
Decoding EEG signals is crucial for unraveling human brain and advancing brain-computer interfaces. Traditional machine learning algorithms have been hindered by the high noise lev…
Delayed Memory Unit: Modelling Temporal Dependency Through Delay Gate
Pengfei Sun, Jibin Wu, Malu Zhang +2
Recurrent Neural Networks (RNNs) are widely recognized for their proficiency in modeling temporal dependencies, making them highly prevalent in sequential data processing applicati…
Adaptive Axonal Delays in feedforward spiking neural networks for accurate spoken word recognition
Pengfei Sun, Ehsan Eqlimi, Yansong Chua +2
Spiking neural networks (SNN) are a promising research avenue for building accurate and efficient automatic speech recognition systems. Recent advances in audio-to-spike encoding a…
Spikemax: Spike-based Loss Methods for Classification
Sumit Bam Shrestha, Longwei Zhu, Pengfei Sun
Spiking Neural Networks~(SNNs) are a promising research paradigm for low power edge-based computing. Recent works in SNN backpropagation has enabled training of SNNs for practical…
Axonal Delay As a Short-Term Memory for Feed Forward Deep Spiking Neural Networks
Pengfei Sun, Longwei Zhu, Dick Botteldooren
The information of spiking neural networks (SNNs) are propagated between the adjacent biological neuron by spikes, which provides a computing paradigm with the promise of simulatin…