LFGP_NeurIPS
importedsoftware/lfgp-neurips
Modeling dynamic functional connectivity with latent factor Gaussian processes
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/modestbayes/LFGP_NeurIPS
- Documentation
- unknown
- Tags
- gaussian-processes · machine-learning · neuroimaging
- Regulatory
- unknown
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- FCEstgaussian-processes · neuroimaging
Methods for estimating time-varying functional connectivity (TVFC)
- GPimgaussian-processes
Gaussian processes and Bayesian optimization for images and hyperspectral data
- Mellongaussian-processes
Non-parametric density inference for single-cell analysis.
- prob-epigaussian-processes
Course materials of "Bayesian Modelling and Probabilistic Programming with Numpyro, and Deep Generative Surrogates for Epidemiology"
- flu-sequence-predictorgaussian-processes
An experimental deep learning & genotype network-based system for predicting new influenza protein sequences.
- 3d_very_deep_vaeneuroimaging
PyTorch implementations of variational autoencoders for 3D images
- api.github.com/repos/modestbayes/LFGP_NeurIPSretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2019-10-24, 5 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/21.json→ .entries["lfgp-neurips"]
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