Ricky Tian Qi Chen

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David DuvenaudAssociate Professor, University of TorontoVerified email at cs.toronto.edu
Yaron LipmanWeizmann Institute, FAIR MetaVerified email at weizmann.ac.il
Yulia RubanovaGoogle DeepmindVerified email at google.com
Maximilian NickelResearch Scientist at FAIR, Meta AIVerified email at meta.com
Brandon AmosMetaVerified email at fb.com
Xuechen LiStanford UniversityVerified email at cs.stanford.edu
Will GrathwohlResearch Scientist, DeepmindVerified email at deepmind.com
Jörn-Henrik JacobsenApple AI/ML ResearchVerified email at vectorinstitute.ai
Jens BehrmannApple AI/ML ResearchVerified email at apple.com
Matthew LeFacebook AI ResearchVerified email at fb.com
Roger GrosseAssociate Professor, University of TorontoVerified email at cs.toronto.edu
Carles Domingo-EnrichMicrosoft ResearchVerified email at nyu.edu
Dinghuai Zhang 张鼎怀Mila, University of MontrealVerified email at mila.quebec
neta shaulComputer Science PhD student, Weizmann Institute of ScienceVerified email at weizmann.ac.il
Mustafa MukadamFAIR, MetaVerified email at meta.com
Aram-Alexandre PooladianNew York UniversityVerified email at nyu.edu
Patrick Kidger"ML Wizard" @ Cradle.bioVerified email at kidger.site
Rodrigo A. Vargas-HernandezAssistant Professor, Chemistry & Chemical Biology, McMaster UniversityVerified email at mcmaster.ca
Brian KarrerResearch Science Manager, MetaVerified email at fb.com
Chin-Wei HuangMicrosoft ResearchVerified email at microsoft.com

Ricky Tian Qi Chen

Other namesRicky T. Q. Chen, Tian Qi Chen

Meta Fundamental AI Research (FAIR)

Verified email at meta.com - Homepage

probabilistic machine learning normalizing flows generative modeling dynamical systems


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, DK Duvenaud Advances in neural information processing systems, 6571-6583, 2018	5371	2018
Isolating Sources of Disentanglement in Variational Autoencoders RTQ Chen, X Li, R Grosse, D Duvenaud Advances in Neural Information Processing Systems, NIPS 2018, 2018	1455	2018
Latent odes for irregularly-sampled time series Y Rubanova, RTQ Chen, D Duvenaud Advances in Neural Information Processing Systems, NeurIPS 2019, 2019	891*	2019
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, ICLR 2019, 2019	881	2019
Invertible residual networks J Behrmann, W Grathwohl, RTQ Chen, D Duvenaud, JH Jacobsen International Conference on Machine Learning, ICML 2019, 2019	667	2019
Fast patch-based style transfer of arbitrary style RTQ Chen, M Schmidt Constructive Machine Learning Workshop, NIPS 2016, 2016	445	2016
Flow Matching for Generative Modeling Y Lipman, RTQ Chen, H Ben-Hamu, M Nickel, M Le International Conference on Learning Representations, ICLR 2023, 2022	444	2022
Residual flows for invertible generative modeling RTQ Chen, J Behrmann, DK Duvenaud, JH Jacobsen Advances in Neural Information Processing Systems, 9913-9923, 2019	392	2019
Scalable gradients for stochastic differential equations X Li, TKL Wong, RTQ Chen, D Duvenaud International Conference on Artificial Intelligence and Statistics, 3870-3882, 2020	321	2020
Scalable reversible generative models with free-form continuous dynamics W Grathwohl, RTQ Chen, J Bettencourt, D Duvenaud International Conference on Learning Representations, 2019	133	2019
Learning Neural Event Functions for Ordinary Differential Equations RTQ Chen, B Amos, M Nickel International Conference on Learning Representations, ICLR 2021, 2021	126	2021
Neural Spatio-Temporal Point Processes RTQ Chen, B Amos, M Nickel International Conference on Learning Representations, ICLR 2021, 2021	99	2021
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization CW Huang, RTQ Chen, C Tsirigotis, A Courville International Conference on Learning Representations, ICLR 2021, 2021	85	2021
Theseus: A Library for Differentiable Nonlinear Optimization L Pineda, T Fan, M Monge, S Venkataraman, P Sodhi, R Chen, J Ortiz, ... Advances in Neural Information Processing Systems, NeurIPS 2022, 2022	80	2022
torchdiffeq, 2018 RTQ Chen URL https://github. com/rtqichen/torchdiffeq 14, 0	78
Scalable gradients and variational inference for stochastic differential equations X Li, TKL Wong, RTQ Chen, DK Duvenaud Symposium on Advances in Approximate Bayesian Inference, 1-28, 2020	70	2020
Multisample Flow Matching: Straightening Flows with Minibatch Couplings AA Pooladian, H Ben-Hamu, C Domingo-Enrich, B Amos, Y Lipman, ... International Conference on Machine Learning, ICML 2023, 2023	64	2023
Riemannian Flow Matching on General Geometries RTQ Chen, Y Lipman ICLR 2024, 2023	62*	2023
“Hey, that’s not an ODE”: Faster ODE Adjoints via Seminorms P Kidger, RTQ Chen, T Lyons International Conference on Machine Learning, ICML 2021, 2021	56*	2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations W Xu, RTQ Chen, X Li, D Duvenaud Artificial Intelligence and Statistics, AISTATS 2022, 2022	52	2022

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