Search Results for author: Marius Hobbhahn

Found 4 papers, 3 papers with code

Compute Trends Across Three Eras of Machine Learning

1 code implementation11 Feb 2022 Jaime Sevilla, Lennart Heim, Anson Ho, Tamay Besiroglu, Marius Hobbhahn, Pablo Villalobos

Since the advent of Deep Learning in the early 2010s, the scaling of training compute has accelerated, doubling approximately every 6 months.

BIG-bench Machine Learning

Laplace Matching for fast Approximate Inference in Generalized Linear Models

1 code implementation7 May 2021 Marius Hobbhahn, Philipp Hennig

We empirically evaluate the method in two different GLMs, showing approximation quality comparable to state-of-the-art approximate inference techniques at a drastic reduction in computational cost.

Bayesian Inference Variational Inference

Fast Predictive Uncertainty for Classification with Bayesian Deep Networks

1 code implementation2 Mar 2020 Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig

We reconsider old work (Laplace Bridge) to construct a Dirichlet approximation of this softmax output distribution, which yields an analytic map between Gaussian distributions in logit space and Dirichlet distributions (the conjugate prior to the Categorical distribution) in the output space.

Classification General Classification

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