Suivre
Ricky Tian Qi Chen
Ricky Tian Qi Chen
Autres nomsRicky T. Q. Chen, Tian Qi Chen
Meta FAIR
Adresse e-mail validée de meta.com - Page d'accueil
Titre
Citée par
Citée par
Année
Neural ordinary differential equations
RTQ Chen, Y Rubanova, J Bettencourt, DK Duvenaud
Advances in neural information processing systems, 6571-6583, 2018
61612018
Isolating Sources of Disentanglement in Variational Autoencoders
RTQ Chen, X Li, R Grosse, D Duvenaud
Advances in Neural Information Processing Systems, NIPS 2018, 2018
15522018
Latent odes for irregularly-sampled time series
Y Rubanova, RTQ Chen, D Duvenaud
Advances in Neural Information Processing Systems, NeurIPS 2019, 2019
1002*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
9532019
Flow Matching for Generative Modeling
Y Lipman, RTQ Chen, H Ben-Hamu, M Nickel, M Le
International Conference on Learning Representations, ICLR 2023, 2022
8362022
Invertible residual networks
J Behrmann, W Grathwohl, RTQ Chen, D Duvenaud, JH Jacobsen
International Conference on Machine Learning, ICML 2019, 2019
7252019
Fast patch-based style transfer of arbitrary style
RTQ Chen, M Schmidt
Constructive Machine Learning Workshop, NIPS 2016, 2016
4662016
Residual flows for invertible generative modeling
RTQ Chen, J Behrmann, DK Duvenaud, JH Jacobsen
Advances in Neural Information Processing Systems, 9913-9923, 2019
4232019
Scalable gradients for stochastic differential equations
X Li, TKL Wong, RTQ Chen, D Duvenaud
International Conference on Artificial Intelligence and Statistics, 3870-3882, 2020
3622020
Scalable reversible generative models with free-form continuous dynamics
W Grathwohl, RTQ Chen, J Bettencourt, D Duvenaud
International Conference on Learning Representations, 2019
1532019
Learning Neural Event Functions for Ordinary Differential Equations
RTQ Chen, B Amos, M Nickel
International Conference on Learning Representations, ICLR 2021, 2021
1412021
Neural Spatio-Temporal Point Processes
RTQ Chen, B Amos, M Nickel
International Conference on Learning Representations, ICLR 2021, 2021
1172021
Riemannian Flow Matching on General Geometries
RTQ Chen, Y Lipman
ICLR 2024, 2023
112*2023
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
1052023
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
972022
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
942021
torchdiffeq, 2018
RTQ Chen
URL https://github. com/rtqichen/torchdiffeq 14, 0
89
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
802020
“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
70*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
602022
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