Alex Immer

Laplace. Laplace approximations for Deep Learning.

heteroscedastic-nn. Code for "Effective Bayesian Heteroscedastic Regression with Deep Neural Networks" (NeurIPS 2023)

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

ntk-marglik. Code for "Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels" at ICML'23

marglik. Marginal likelihood estimation for model selection in deep learning

ppygis3. PostGIS geometry objects in python

loci. Estimation of Causal Location-Scale Noise Models

FWDL. Frank Wolfe for Deep Learning

run-dmc. Solution repository of DMC-16 finalist team

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

VolkSwaggen. Swaggen bei Volkswagen

SwellBoard. TypeScript

VIND. Variational Inference with Numerical Derivatives: variance reduction through coupling

RDFs-from-wikitables. Generating RDFs from wikitables using the wikitables-package