Repairing the neural highway

Artificial Neural Networks for Repairing Language

Spontaneous language contains many discontinuities caused by unusual order, false starts, repairs, repetitions, pauses, etc. Since data-driven artificial neural networks possess an inherent fault tolerance we use this property for dealing with such forms of “sequential noise”. We describe an approach for a flat syntactic and semantic interpretation of ill-formed utterances in spontaneous dialog...

Neural stem cell-mediated immunomodulation: repairing the haemorrhagic brain.

Neural stem/precursor cells (NPCs) are broadly proposed as an alternative cell source to repair brain damage upon transplantation. NPC-driven brain repair has variably been shown in several pre-clinical models of neurological disorders. However, a comprehensive knowledge of the different mechanism(s) by which such cells exert their therapeutic potential is still lacking. While the replacement o...

Highway Vehicle Classification by Probabilistic Neural Networks

The Federal Highway Administration (FHWA) Office of Highway Planning requires states to furnish vehicle classification data as part of the Highway Performance Monitoring Systems (HPMS). To comply with this requirement, most states use the “F-Scheme” to classify vehicles. This scheme classifies vehicles in 13 classes depending on a number of factors, primarily the number of axles and the axle sp...

Neural Choice by Elimination via Highway Networks

We introduce Neural Choice by Elimination, a new framework that integrates deep neural networks into probabilistic sequential choice models for learning to rank. Given a set of items to chose from, the elimination strategy starts with the whole item set and iteratively eliminates the least worthy item in the remaining subset. We prove that the choice by elimination is equivalent to marginalizin...

Highway Engineering Highway Engineering