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12/21/2022
Scalable Hybrid Learning Techniques for Scientific Data Compression
Data compression is becoming critical for storing scientific data becaus...
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06/01/2021
Hybrid Generative Models for Two-Dimensional Datasets
Two-dimensional array-based datasets are pervasive in a variety of domai...
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01/04/2019
Intelligent Intersection: Two-Stream Convolutional Networks for Real-time Near Accident Detection in Traffic Video
In Intelligent Transportation System, real-time systems that monitor and...
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07/06/2018
Dynamic Load Balancing for Compressible Multiphase Turbulence
CMT-nek is a new scientific application for performing high fidelity pre...
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05/18/2018
Learning Permutations with Sinkhorn Policy Gradient
Many problems at the intersection of combinatorics and computer science ...
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03/07/2018
Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification
We develop three efficient approaches for generating visual explanations...
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02/19/2018
Machine Learning Methods for Solving Assignment Problems in Multi-Target Tracking
Data association and track-to-track association, two fundamental problem...
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02/11/2018
Global Model Interpretation via Recursive Partitioning
In this work, we propose a simple but effective method to interpret blac...
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01/21/2016
Spatial Scaling of Satellite Soil Moisture using Temporal Correlations and Ensemble Learning
A novel algorithm is developed to downscale soil moisture (SM), obtained...
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01/20/2016
Disaggregation of SMAP L3 Brightness Temperatures to 9km using Kernel Machines
In this study, a machine learning algorithm is used for disaggregation o...
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01/30/2015
Downscaling Microwave Brightness Temperatures Using Self Regularized Regressive Models
A novel algorithm is proposed to downscale microwave brightness temperat...
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01/30/2015