Results 141 to 150 of about 7,675,115 (371)
One weird trick for parallelizing convolutional neural networks [PDF]
arXiv, 2014 I present a new way to parallelize the training of convolutional neural networks across multiple GPUs. The method scales significantly better than all alternatives when applied to modern convolutional neural networks.
arxiv
Analysis of the Neural Network Regulating the Cardio-Renal System in the Central Nervous System ofHelix pomatiaL. [PDF]
, 1979 Katalin S.-Rózsa
openalex +1 more source
, 2018 We present N2Net, a system that implements binary neural networks using commodity switching chips deployed in network switches and routers. Our system shows that these devices can run simple neural network models, whose input is encoded in the network packets' header, at packet processing speeds (billions of packets per second).
Siracusano, Giuseppe, Bifulco, Roberto
openaire +2 more sources
Translating Muscle RNAseq Into the Clinic for the Diagnosis of Muscle Diseases
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Approximately half of patients with hereditary myopathies remain without a definitive genetic diagnosis after DNA next‐generation sequencing (NGS). Here, we implemented transcriptome analysis of muscle biopsies as a complementary diagnostic tool for patients with muscle disease but no definitive genetic diagnosis after exome ...
Alba Segarra‐Casas +24 more
wiley +1 more source
Nonlinear Systems Identification Using Deep Dynamic Neural Networks [PDF]
arXiv, 2016 Neural networks are known to be effective function approximators. Recently, deep neural networks have proven to be very effective in pattern recognition, classification tasks and human-level control to model highly nonlinear realworld systems. This paper investigates the effectiveness of deep neural networks in the modeling of dynamical systems with ...
arxiv
Pathway Analyses of Inherited Neuropathies Identify Putative Common Mechanisms of Axon Degeneration
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Inherited neuropathies (IN) are associated with over 100 different genetic mutations presenting with a variety of phenotypes. This complexity suggests multiple pathways may converge onto a limited number of downstream pathways to effect axonal injury.
Christopher R. Cashman +2 more
wiley +1 more source
Hybrid Quantum-Classical Neural Networks for Downlink Beamforming Optimization [PDF]
arXivThis paper investigates quantum machine learning to optimize the beamforming in a multiuser multiple-input single-output downlink system. We aim to combine the power of quantum neural networks and the success of classical deep neural networks to enhance the learning performance.
arxiv
Geometric Decomposition of Feed Forward Neural Networks [PDF]
arXiv, 2016 There have been several attempts to mathematically understand neural networks and many more from biological and computational perspectives. The field has exploded in the last decade, yet neural networks are still treated much like a black box. In this work we describe a structure that is inherent to a feed forward neural network.
arxiv
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To provide a comprehensive clinical and genetic characterization of individuals with arthrogryposis multiplex congenita (AMC), focusing on the distribution of genetic etiologies across the neuromuscular spectrum and comparing myogenic and neurogenic subtypes. Methods A total of 105 individuals with AMC were clinically and genetically
Florencia Pérez‐Vidarte +13 more
wiley +1 more source