Search Results for author:
Found 15 papers, 4 papers with code
Learned Incremental Representations for Parsing
We present an incremental syntactic representation that consists of assigning a single discrete label to each word in a sentence, where the label is predicted using strictly incremental processing of a prefix of the sentence, and the sequence of labels for a sentence fully determines a parse tree.
CiwaGAN: Articulatory information exchange
This paper introduces CiwaGAN, a model of human spoken language acquisition that combines unsupervised articulatory modeling with an unsupervised model of information exchange through the auditory modality.
Basic syntax from speech: Spontaneous concatenation in unsupervised deep neural networks
Computational models of syntax are predominantly text-based.
AI-assisted coding: Experiments with GPT-4
We report several experiments using GPT-4 to generate computer code.
Device Image-IV Mapping using Variational Autoencoder for Inverse Design and Forward Prediction
Since manifold learning is used, the machine is shown to be robust against noise in the inputs (i. e. using hand-drawn images and noisy IDVG curves) and not confused by weak and irrelevant independent variables.
Remote estimation of geologic composition using interferometric synthetic-aperture radar in California's Central Valley
We also achieved significant accuracy with 1/4 sparse sampling to reduce any spatial correlations among data, suggesting that the model has the potential to be generalized to other regions for indirect estimation of geologic composition.
Material Prediction for Design Automation Using Graph Representation Learning
Successful material selection is critical in designing and manufacturing products for design automation.
Neurosymbolic hybrid approach to driver collision warning
(2) A mediated hybrid recognition system in which a system is created by combining independent modules that detect each semantic feature.
Explainability Tools Enabling Deep Learning in Future In-Situ Real-Time Planetary Explorations
It provides a set of explainability tools (ET) that opens the black box of a DNN so that the individual contribution of neurons to category classification can be ranked and visualized.
Small Target Detection for Search and Rescue Operations using Distributed Deep Learning and Synthetic Data Generation
We compared the performance between the auto-detection system and the human eye.
Improved visible to IR image transformation using synthetic data augmentation with cycle-consistent adversarial networks
In summary, CycleGAN is used with synthetic data to improve the IR image conversion performance of visible images.
Deep Neural Networks for Pattern Recognition
In the field of pattern recognition research, the method of using deep neural networks based on improved computing hardware recently attracted attention because of their superior accuracy compared to conventional methods.
Automatic speech recognition for launch control center communication using recurrent neural networks with data augmentation and custom language model
Transcribing voice communications in NASA's launch control center is important for information utilization.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Occluded object reconstruction for first responders with augmented reality glasses using conditional generative adversarial networks
We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts.
Predicting Rapid Fire Growth (Flashover) Using Conditional Generative Adversarial Networks
A flashover occurs when a fire spreads very rapidly through crevices due to intense heat.
