David Duvenaud

Cited by

	All	Since 2019
Citations	30748	28070
h-index	51	51
i10-index	73	69

6000

3000

1500

4500

2015201620172018201920202021202220232024145 280 631 1388 2463 3907 4950 5248 5951 5530

Public access

View all

14 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Ryan P. AdamsPrinceton UniversityVerified email at princeton.edu
Ricky Tian Qi ChenMeta FAIRVerified email at meta.com
Alan Aspuru-GuzikProfessor of Chemistry and Computer Science, University of Toronto (starting July 1, 2018)Verified email at utoronto.ca
Dougal MaclaurinPhD student, Harvard UniversityVerified email at physics.harvard.edu
Jorge Aguilera-IparraguirreRecursion PharmaceuticalsVerified email at recursionpharma.com
Will GrathwohlResearch Scientist, DeepmindVerified email at deepmind.com
Rafael Gómez-BombarelliAssociate Professor, MIT DMSEVerified email at mit.edu
Jesse BettencourtUniversity of TorontoVerified email at cs.toronto.edu
Roger GrosseAssociate Professor, University of TorontoVerified email at cs.toronto.edu
Yulia RubanovaGoogle DeepmindVerified email at google.com
Jonathan LorraineResearch Scientist, NVIDIA; PhD, University of TorontoVerified email at cs.toronto.edu
Jörn-Henrik JacobsenApple AI/ML ResearchVerified email at vectorinstitute.ai
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Xuechen LiStanford UniversityVerified email at cs.stanford.edu
Jennifer N WeiOpen Molecular Software FoundationVerified email at omsf.io
Kevin SwerskyGoogle BrainVerified email at cs.toronto.edu
Joshua B. TenenbaumMITVerified email at mit.edu
James Robert LloydPhD from Machine Learning Group, Cambridge UniversityVerified email at cam.ac.uk
José Miguel Hernández-LobatoProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
Matthew J. JohnsonGoogle BrainVerified email at csail.mit.edu

David Duvenaud

Associate Professor, University of Toronto

Verified email at cs.toronto.edu - Homepage

Deep Learning Differential Equations Approximate Inference


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Neural Ordinary Differential Equations RTQ Chen, Y Rubanova, J Bettencourt, D Duvenaud Neural Information Processing Systems, 2018	5652	2018
Convolutional Networks on Graphs for Learning Molecular Fingerprints D Duvenaud, D Maclaurin, J Aguilera-Iparraguirre, R Gómez-Bombarelli, ... Neural Information Processing Systems, 2015	4450	2015
Automatic chemical design using a data-driven continuous representation of molecules R Gómez-Bombarelli, JN Wei, D Duvenaud, JM Hernández-Lobato, ... ACS central science 4 (2), 268-276, 2018	3506	2018
Isolating sources of disentanglement in variational autoencoders RTQ Chen, X Li, R Grosse, D Duvenaud Neural Information Processing Systems, arXiv preprint arXiv:1802.04942, 2018	1495	2018
Gradient-based hyperparameter optimization through reversible learning D Maclaurin, D Duvenaud, R Adams International conference on machine learning, 2113-2122, 2015	1099	2015
FFJORD: Free-form continuous dynamics for scalable reversible generative models W Grathwohl, RTQ Chen, J Betterncourt, I Sutskever, D Duvenaud International Conference on Learning Representations, 2018	1039*	2018
Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach R Gómez-Bombarelli, J Aguilera-Iparraguirre, TD Hirzel, D Duvenaud, ... Nature materials 15 (10), 1120-1127, 2016	997	2016
Latent ODEs for irregularly-sampled time series Y Rubanova, RTQ Chen, D Duvenaud Neural Information Processing Systems, 2019	936*	2019
Automatic model construction with Gaussian processes D Duvenaud	935	2014
Invertible residual networks J Behrmann, W Grathwohl, RTQ Chen, D Duvenaud, JH Jacobsen International Conference on Machine Learning, 2018	687	2018
Structure Discovery in Nonparametric Regression through Compositional Kernel Search D Duvenaud, JR Lloyd, R Grosse, JB Tenenbaum, Z Ghahramani International Conference on Machine Learning, 2013	649	2013
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One W Grathwohl, KC Wang, JH Jacobsen, D Duvenaud, M Norouzi, ... International Conference on Learning Representations 2020, 2019	609	2019
Composing graphical models with neural networks for structured representations and fast inference MJ Johnson, DK Duvenaud, A Wiltschko, RP Adams, SR Datta Advances in neural information processing systems 29, 2016	557	2016
Neural networks for the prediction of organic chemistry reactions JN Wei, D Duvenaud, A Aspuru-Guzik ACS central science 2 (10), 725-732, 2016	473	2016
Additive Gaussian Processes D Duvenaud, H Nickisch, CE Rasmussen Neural Information Processing Systems, 2011	435	2011
Optimizing Millions of Hyperparameters by Implicit Differentiation J Lorraine, P Vicol, D Duvenaud Artificial Intelligence and Statistics, 2019	425	2019
Scalable Gradients for Stochastic Differential Equations X Li, TKL Wong, RTQ Chen, D Duvenaud Artificial Intelligence and Statistics, 2020	411*	2020
Residual Flows for Invertible Generative Modeling RTQ Chen, J Behrmann, D Duvenaud, JH Jacobsen Neural Information Processing Systems, 2019	404	2019
Autograd: Reverse-mode differentiation of native python D Maclaurin, D Duvenaud, M Johnson, RP Adams ICML workshop on Automatic Machine Learning, 2015	381*	2015
Efficient Graph Generation with Graph Recurrent Attention Networks R Liao, Y Li, Y Song, S Wang, C Nash, WL Hamilton, D Duvenaud, ... Neural Information Processing Systems, 2019	367	2019

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow

Cited by

Co-authors