Search Results for author:
Found 6 papers, 3 papers with code
DeepSZ: Identification of Sunyaev-Zel'dovich Galaxy Clusters using Deep Learning
We present a comparison between two methods of cluster identification: the standard Matched Filter (MF) method in SZ cluster finding and a method using Convolutional Neural Networks (CNN).
Deeply Uncertain: Comparing Methods of Uncertainty Quantification in Deep Learning Algorithms
We present a comparison of methods for uncertainty quantification (UQ) in deep learning algorithms in the context of a simple physical system.
Restricted Boltzmann Machines for galaxy morphology classification with a quantum annealer
We present the application of Restricted Boltzmann Machines (RBMs) to the task of astronomical image classification using a quantum annealer built by D-Wave Systems.
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era
The field of astronomy has arrived at a turning point in terms of size and complexity of both datasets and scientific collaboration.
Improving Traffic Safety Through Video Analysis in Jakarta, Indonesia
This project presents the results of a partnership between the Data Science for Social Good fellowship, Jakarta Smart City and Pulse Lab Jakarta to create a video analysis pipeline for the purpose of improving traffic safety in Jakarta.
DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with Deep Neural Networks
In this work, we demonstrate reconstruction of the CMB lensing potential with deep convolutional neural networks (CNN) - ie, a ResUNet.
