disperse's People
disperse's Issues
Datasets
Assemble on nersc:
-- Ilustris
-- Tracing Cosmic Web
-- GAMA (volume limited, https://arxiv.org/pdf/1409.4681.pdf)
-- Abacus cubic boxes + GAMA with known environment features
-- Camels (https://arxiv.org/abs/2111.08683)
Prediction: Graph neural networks
Graph neural networks with pytorch:
http://tkipf.github.io/graph-convolutional-networks/
https://www.pyg.org/news/index/
https://github.com/pyg-team/pytorch_geometric/
https://towardsdatascience.com/graph-neural-networks-in-python-c310c7c18c83/
Application to Camels:
https://arxiv.org/abs/2111.08683/
Features
-- Voronoi density
-- Tidal stuff
-- Networkx: degree -> number of connections; centrality; anisotropy / Inertial tensor?
-- Topological bias, https://arxiv.org/abs/2206.14655
Classification:
Classification of galaxy properties into labels:
-- Laplacian eigenmaps
https://www.sjsu.edu/faculty/guangliang.chen/Math253S20/lec12laplacian.pdf
https://scikit-learn.org/stable/modules/generated/sklearn.manifold.SpectralEmbedding.html
https://www2.imm.dtu.dk/projects/manifold/Papers/Laplacian.pdf
-- SOM
-- tSNE
https://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding
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