Ishita Tandon, Vitali Maldonado, Megan Wilkerson, Amanda Walls, Raj R Rao, Mostafa Elsaadany
Immersive virtual reality-based learning as a supplement for biomedical engineering labs: challenges faced and lessons learned
Frontiers in medical technology
learning neural networks poses peculiar challenges using discretized rather continuous synaptic states choice discrete synapses motivated biological reasoning experiments possibly hardware implementation considerations well paper extend previous large deviations analysis unveiled existence peculiar dense regions space synaptic states accounts possibility learning efficiently networks binary synapses extend analysis synapses multiple states generally plausible biological features results clearly indicate overall qualitative picture unchanged respect binary case robust variation details model also provide quantitative results suggest advantages increasing synaptic precision ie number internal synaptic states rapidly vanish first bits therefore practical applications bits may needed nearoptimal performance consistent recent biological findings finally demonstrate theoretical analysis exploited design efficient algorithmic search strategies