Laplace approximations for Deep Learning.
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Oct 9, 2024 - Python
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approximate-bayesian-inference
Here are 9 public repositories matching this topic...
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
machine-learning
signal-processing
gaussian-processes
state-space-models
jax
approximate-bayesian-inference
sparse-gps
markov-gps
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Dec 22, 2023 - Python
distributed, likelihood-free inference
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Oct 30, 2024 - Python
Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
machine-learning
signal-processing
gaussian-processes
state-space-models
kalman-smoother
approximate-bayesian-inference
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Jul 6, 2023 - Jupyter Notebook
A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural networks and hierarchical distribution (ICML 2018).
mcmc
uncertainty-quantification
variational-inference
variational-autoencoder
implicit-modeling
implicit-flow
approximate-bayesian-inference
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Oct 16, 2024 - MATLAB
Bayesian Learning and Neural Networks (jupyter book sources)
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Apr 18, 2023 - Jupyter Notebook
Generative Models
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May 8, 2018
Likelihood-Free Inference for Julia.
abc
likelihood-free
approximate-bayesian-computation
approximate-bayesian-inference
likelihood-free-inference
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Mar 14, 2022 - Julia
Approximate Bayesian Computation algorithm based on simulated annealing
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Updated
Nov 8, 2024 - Julia
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