Search Results for author: Eric Meissner

Found 3 papers, 1 papers with code

Modular Deep Probabilistic Programming

1 code implementation ICLR 2019 Zhenwen Dai, Eric Meissner, Neil D. Lawrence

A probabilistic module consists of a set of random variables with associated probabilistic distributions and dedicated inference methods.

Probabilistic Programming Variational Inference

Auto-Differentiating Linear Algebra

no code implementations24 Oct 2017 Matthias Seeger, Asmus Hetzel, Zhenwen Dai, Eric Meissner, Neil D. Lawrence

Development systems for deep learning (DL), such as Theano, Torch, TensorFlow, or MXNet, are easy-to-use tools for creating complex neural network models.

Active Learning Gaussian Processes

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