ML Anthology

Duvenaud, David K.

17 publications

NeurIPS 2023 Tools for Verifying Neural Models' Training Data Dami Choi, Yonadav Shavit, David K. Duvenaud
NeurIPS 2021 Meta-Learning to Improve Pre-Training Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David K. Duvenaud
NeurIPS 2020 Learning Differential Equations That Are Easy to Solve Jacob Kelly, Jesse Bettencourt, Matthew J Johnson, David K. Duvenaud
NeurIPS 2020 What Went Wrong and When? Instance-Wise Feature Importance for Time-Series Black-Box Models Sana Tonekaboni, Shalmali Joshi, Kieran Campbell, David K. Duvenaud, Anna Goldenberg
NeurIPS 2019 Efficient Graph Generation with Graph Recurrent Attention Networks Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Will Hamilton, David K. Duvenaud, Raquel Urtasun, Richard Zemel
NeurIPS 2019 Latent Ordinary Differential Equations for Irregularly-Sampled Time Series Yulia Rubanova, Ricky T. Q. Chen, David K. Duvenaud
NeurIPS 2019 Neural Networks with Cheap Differential Operators Ricky T. Q. Chen, David K. Duvenaud
NeurIPS 2019 Residual Flows for Invertible Generative Modeling Ricky T. Q. Chen, Jens Behrmann, David K. Duvenaud, Joern-Henrik Jacobsen
NeurIPS 2018 Isolating Sources of Disentanglement in Variational Autoencoders Ricky T. Q. Chen, Xuechen Li, Roger B Grosse, David K. Duvenaud
NeurIPS 2018 Neural Ordinary Differential Equations Ricky T. Q. Chen, Yulia Rubanova, Jesse Bettencourt, David K. Duvenaud
NeurIPS 2017 Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference Geoffrey Roeder, Yuhuai Wu, David K. Duvenaud
NeurIPS 2016 Composing Graphical Models with Neural Networks for Structured Representations and Fast Inference Matthew J Johnson, David K. Duvenaud, Alex Wiltschko, Ryan P. Adams, Sandeep R Datta
NeurIPS 2016 Probing the Compositionality of Intuitive Functions Eric Schulz, Josh Tenenbaum, David K. Duvenaud, Maarten Speekenbrink, Samuel J Gershman
NeurIPS 2015 Convolutional Networks on Graphs for Learning Molecular Fingerprints David K. Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alan Aspuru-Guzik, Ryan P. Adams
NeurIPS 2014 Probabilistic ODE Solvers with Runge-Kutta Means Michael Schober, David K. Duvenaud, Philipp Hennig
NeurIPS 2012 Active Learning of Model Evidence Using Bayesian Quadrature Michael Osborne, Roman Garnett, Zoubin Ghahramani, David K. Duvenaud, Stephen J. Roberts, Carl E. Rasmussen
NeurIPS 2011 Additive Gaussian Processes David K. Duvenaud, Hannes Nickisch, Carl E. Rasmussen