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  "Title": "Latent Binary Bayesian Neural Networks Using 'torch'",
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  "Description": "Latent binary Bayesian neural networks (LBBNNs) are\nimplemented using 'torch', an R interface to the LibTorch\nbackend. Supports mean-field variational inference as well as\nflexible variational posteriors using normalizing flows. The\nstandard LBBNN implementation follows Hubin and Storvik (2024)\n<doi:10.3390/math12060788>, using the local reparametrization\ntrick as in Skaaret-Lund et al. (2024)\n<https://openreview.net/pdf?id=d6kqUKzG3V>. Input-skip\nconnections are also supported, as described in Høyheim et al.\n(2025) <doi:10.48550/arXiv.2503.10496>.",
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