Second Order Optimization and Curvature Estimation with K-FAC in JAX.
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Updated
Jun 7, 2024 - Python
Second Order Optimization and Curvature Estimation with K-FAC in JAX.
Effortless Bayesian Deep Learning through Laplace Approximation for Flux.jl neural networks.
Bayesian Deep Learning: A Survey
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Variational continual learning of a conditional diffusion model to generate MNIST. Based on 'Conditional Diffusion MNIST'.
Code accompanying ICLR 2024 paper "Function-space Parameterization of Neural Networks for Sequential Learning"
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Research-repository: Bayesian neural networks for predicting disruptions using EFIT and diagnostic data in KSTAR
[NeurIPS 2023] Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing
Adaptive Conditional Quantile Neural Processes - PyTorch
BayeSeg: Bayesian Modelling for Medical Image Segmentation with Interpretable Generalizability
Open Source Photometric classification https://supernnova.readthedocs.io
Codebase for BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts.
A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
PheSeq, A Bayesian Deep Learning Model to Enhance and Interpret the Gene Disease Association Studies
Bayesian deep learning for remaining useful life estimation via Stein variational gradient descent
ProbVLM: Probabilistic Adapter for Frozen Vision-Language Models
Notes and Experiments with Probabilistic Deep Learning Models
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