Ricky Tian Qi Chen
Ricky Tian Qi Chen
Zweryfikowany adres z cs.toronto.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Neural ordinary differential equations
RTQ Chen, Y Rubanova, J Bettencourt, DK Duvenaud
Advances in neural information processing systems, 6571-6583, 2018
11002018
Isolating Sources of Disentanglement in Variational Autoencoders
RTQ Chen, X Li, R Grosse, D Duvenaud
NIPS 2018, 2018
4442018
FFJORD: Free-form continuous dynamics for scalable reversible generative models
W Grathwohl, RTQ Chen, J Betterncourt, I Sutskever, D Duvenaud
ICLR 2019, 2018
2862018
Fast patch-based style transfer of arbitrary style
RTQ Chen, M Schmidt
Constructive Machine Learning Workshop, NIPS 2016, 2016
2042016
Invertible residual networks
J Behrmann, W Grathwohl, RTQ Chen, D Duvenaud, JH Jacobsen
ICML 2019, 2018
1932018
Residual flows for invertible generative modeling
RTQ Chen, J Behrmann, DK Duvenaud, JH Jacobsen
Advances in Neural Information Processing Systems, 9913-9923, 2019
962019
Latent ordinary differential equations for irregularly-sampled time series
Y Rubanova, RTQ Chen, DK Duvenaud
Advances in Neural Information Processing Systems, 5320-5330, 2019
922019
Latent odes for irregularly-sampled time series
Y Rubanova, RTQ Chen, D Duvenaud
arXiv preprint arXiv:1907.03907, 2019
612019
Scalable gradients for stochastic differential equations
X Li, TKL Wong, RTQ Chen, D Duvenaud
International Conference on Artificial Intelligence and Statistics, 3870-3882, 2020
472020
Scalable reversible generative models with free-form continuous dynamics
W Grathwohl, RTQ Chen, J Bettencourt, D Duvenaud
International Conference on Learning Representations, 2019
282019
SUMO: Unbiased estimation of log marginal probability for latent variable models
Y Luo, A Beatson, M Norouzi, J Zhu, D Duvenaud, RP Adams, RTQ Chen
ICLR 2020, 2020
112020
Neural networks with cheap differential operators
RTQ Chen, D Duvenaud
Advances in Neural Information Processing Systems, 9961-9971, 2019
112019
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
62020
Learning Neural Event Functions for Ordinary Differential Equations
RTQ Chen, B Amos, M Nickel
ICLR 2021, 2020
22020
" Hey, that's not an ODE": Faster ODE Adjoints with 12 Lines of Code
P Kidger, RTQ Chen, T Lyons
arXiv preprint arXiv:2009.09457, 2020
22020
Learning Motion Predictors for Smart Wheelchair using Autoregressive Sparse Gaussian Process
Z Fan, L Meng, RTQ Chen, J Li, IM Mitchell
ICRA 2018, 2017
22017
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
CW Huang, RTQ Chen, C Tsirigotis, A Courville
ICLR 2021, 2020
12020
Neural Spatio-Temporal Point Processes
RTQ Chen, B Amos, M Nickel
ICLR 2021, 2020
12020
Self-Tuning Stochastic Optimization with Curvature-Aware Gradient Filtering
RTQ Chen, D Choi, L Balles, D Duvenaud, P Hennig
Workshop on "I Can't Believe It's Not Better!", NeurIPS 2020, 2020
12020
Fully differentiable optimization protocols for non-equilibrium steady states
RA Vargas-Hernández, RTQ Chen, KA Jung, P Brumer
arXiv preprint arXiv:2103.12604, 2021
2021
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