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*David Duvenaud* Automatic Differentiation: The most criminally underused tool in probabilistic numerics
David Duvenaud
Author Information
David Duvenaud (University of Toronto)
More from the Same Authors
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2021 Poster: Meta-learning to Improve Pre-training »
Aniruddh Raghu · Jonathan Lorraine · Simon Kornblith · Matthew McDermott · David Duvenaud -
2016 : Generating Class-conditional Images with Gradient-based Inference »
David Duvenaud -
2016 : David Duvenaud – No more mini-languages: The power of autodiffing full-featured Python »
David Duvenaud -
2016 Workshop: Reliable Machine Learning in the Wild »
Dylan Hadfield-Menell · Adrian Weller · David Duvenaud · Jacob Steinhardt · Percy Liang -
2016 Poster: Composing graphical models with neural networks for structured representations and fast inference »
Matthew Johnson · David Duvenaud · Alex Wiltschko · Ryan Adams · Sandeep R Datta -
2016 Poster: Probing the Compositionality of Intuitive Functions »
Eric Schulz · Josh Tenenbaum · David Duvenaud · Maarten Speekenbrink · Samuel J Gershman -
2015 Poster: Convolutional Networks on Graphs for Learning Molecular Fingerprints »
David Duvenaud · Dougal Maclaurin · Jorge Iparraguirre · Rafael Bombarell · Timothy Hirzel · Alan Aspuru-Guzik · Ryan Adams -
2014 Poster: Probabilistic ODE Solvers with Runge-Kutta Means »
Michael Schober · David Duvenaud · Philipp Hennig -
2014 Oral: Probabilistic ODE Solvers with Runge-Kutta Means »
Michael Schober · David Duvenaud · Philipp Hennig -
2012 Poster: Active Learning of Model Evidence Using Bayesian Quadrature »
Michael A Osborne · David Duvenaud · Roman Garnett · Carl Edward Rasmussen · Stephen J Roberts · Zoubin Ghahramani -
2011 Poster: Additive Gaussian Processes »
David Duvenaud · Hannes Nickisch · Carl Edward Rasmussen