384 citations · 650 across the 17 of their papers we have counts for
5 papers · 1 filter
ApproxDBN: Approximate Computing for Discriminative Deep Belief Networks
Xiaojing Xu, Srinjoy Das, Ken Kreutz-Delgado
Probabilistic generative neural networks are useful for many applications, such as image classification, speech recognition and occlusion removal. However, the power budget for har…
A Nonparametric Framework for Quantifying Generative Inference on Neuromorphic Systems
Ojash Neopane, Srinjoy Das, Ery Arias-Castro +1
Restricted Boltzmann Machines and Deep Belief Networks have been successfully used in probabilistic generative model applications such as image occlusion removal, pattern completio…
Mapping Generative Models onto a Network of Digital Spiking Neurons
Bruno U. Pedroni, Srinjoy Das, John V. Arthur +5
Stochastic neural networks such as Restricted Boltzmann Machines (RBMs) have been successfully used in applications ranging from speech recognition to image classification. Inferen…
Gibbs Sampling with Low-Power Spiking Digital Neurons
Srinjoy Das, Bruno Umbria Pedroni, Paul Merolla +6
Restricted Boltzmann Machines and Deep Belief Networks have been successfully used in a wide variety of applications including image classification and speech recognition. Inferenc…
Event-Driven Contrastive Divergence for Spiking Neuromorphic Systems
Emre Neftci, Srinjoy Das, Bruno Pedroni +2
Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as dimensionality reduction, feature…