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cs.LG2025
Traces Propagation: Memory-Efficient and Scalable Forward-Only Learning in Spiking Neural Networks
Lorenzo Pes, Bojian Yin, Sander Stuijk +1
Spiking Neural Networks (SNNs) provide an efficient framework for processing dynamic spatio-temporal signals and for investigating the learning principles underlying biological neu…
cs.LG2024
Probabilistic Inference in the Era of Tensor Networks and Differential Programming
Martin Roa-Villescas, Xuanzhao Gao, Sander Stuijk +2
Probabilistic inference is a fundamental task in modern machine learning. Recent advances in tensor network (TN) contraction algorithms have enabled the development of better exact…