3 papers
cs.NE2026
STEMS: Spatial-Temporal Mapping For Spiking Neural Networks
Sherif Eissa, Sander Stuijk, Floran De Putter +3
Spiking Neural Networks (SNNs) are promising bio-inspired third-generation neural networks. Recent research has trained deep SNN models with accuracy on par with Artificial Neural…
cs.CV2025
Sparse Convolutional Recurrent Learning for Efficient Event-based Neuromorphic Object Detection
Shenqi Wang, Yingfu Xu, Amirreza Yousefzadeh +4
Leveraging the high temporal resolution and dynamic range, object detection with event cameras can enhance the performance and safety of automotive and robotics applications in rea…
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…