neuromorphic computing
An approach to computing that mimics the architecture and functioning of the human brain, aiming to achieve efficient processing through the use of specialized hardware designed for parallel computation and low power consumption.
- Adaptive Surrogate Gradients for Sequential Reinforcement Learning in Spiking Neural Networks
- Adaptive Surrogate Gradients for Sequential Reinforcement Learning in Spiking Neural Networks
- Stochastic Forward-Forward Learning through Representational Dimensionality Compression
- Unveiling the Spatial-temporal Effective Receptive Fields of Spiking Neural Networks