J.B. Moore
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View article: Using matrix-product states for time-series machine learning
Using matrix-product states for time-series machine learning Open
Matrix-product states (MPS) have proven to be a versatile ansatz for modeling quantum many-body physics. For many applications, and particularly in one-dimension, they capture relevant quantum correlations in many-body wave functions while…
View article: MPSTime.jl Paper Code
MPSTime.jl Paper Code Open
A snapshot of the "minimal_itensor" branch of MPSTime.jl which contains all code and datasets used to produce the results in the paper "Using matrix-product states for time-series machine learning".
View article: Segmentation of cortical bone, trabecular bone, and medullary pores from micro‐ <scp>CT</scp> images using <scp>2D</scp> and <scp>3D</scp> deep learning models
Segmentation of cortical bone, trabecular bone, and medullary pores from micro‐ <span>CT</span> images using <span>2D</span> and <span>3D</span> deep learning models Open
Computed tomography (CT) enables rapid imaging of large‐scale studies of bone, but those datasets typically require manual segmentation, which is time‐consuming and prone to error. Convolutional neural networks (CNNs) offer an automated so…