aleximmer

BNN-predictions

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

FWDL

Frank Wolfe for Deep Learning

heteroscedastic-nn

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

Laplace

Laplace approximations for Deep Learning.

loci

Estimation of Causal Location-Scale Noise Models

marglik

Marginal likelihood estimation for model selection in deep learning

ntk-marglik

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

ppygis3

PostGIS geometry objects in python

run-dmc

Solution repository of DMC-16 finalist team

dnn2gp

Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)

aleximmer/Laplace

Laplace approximations for Deep Learning.

aleximmer/BNN-predictions

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

aleximmer/heteroscedastic-nn

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

aleximmer/marglik

Marginal likelihood estimation for model selection in deep learning

aleximmer/ppygis3

PostGIS geometry objects in python

aleximmer/FWDL

Frank Wolfe for Deep Learning

aleximmer/ntk-marglik

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

aleximmer/loci

Estimation of Causal Location-Scale Noise Models

aleximmer/run-dmc

Solution repository of DMC-16 finalist team

aleximmer/VolkSwaggen

Swaggen bei Volkswagen

aleximmer/WikitablesToTriples

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

aleximmer/SwellBoard

aleximmer/RDFs-from-wikitables

Generating RDFs from wikitables using the wikitables-package

aleximmer/VIND

Variational Inference with Numerical Derivatives: variance reduction through coupling

aleximmer/network-epistemology

aleximmer/pdoc

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