Beast code in Giters

Alex Immer's repositories

Laplace approximations for Deep Learning.

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Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021

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Code for "Effective Bayesian Heteroscedastic Regression with Deep Neural Networks" (NeurIPS 2023)

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Marginal likelihood estimation for model selection in deep learning

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PostGIS geometry objects in python

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Frank Wolfe for Deep Learning

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Code for "Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels" at ICML'23

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Estimation of Causal Location-Scale Noise Models

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Solution repository of DMC-16 finalist team

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Swaggen bei Volkswagen

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Extractor for structured knowledge from Wikipedia's tables written in python

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Generating RDFs from wikitables using the wikitables-package

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Variational Inference with Numerical Derivatives: variance reduction through coupling

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:snake: :arrow_right: :scroll: Auto-generate API documentation for Python projects

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