Ricky Tian Qi Chen
Ricky Tian Qi Chen
Verified email at cs.toronto.edu - Homepage
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
8032018
Isolating Sources of Disentanglement in Variational Autoencoders
RTQ Chen, X Li, R Grosse, D Duvenaud
NIPS 2018, 2018
3582018
FFJORD: Free-form continuous dynamics for scalable reversible generative models
W Grathwohl, RTQ Chen, J Betterncourt, I Sutskever, D Duvenaud
ICLR 2019, 2018
2252018
Fast patch-based style transfer of arbitrary style
RTQ Chen, M Schmidt
Constructive Machine Learning Workshop, NIPS 2016, 2016
1732016
Invertible residual networks
J Behrmann, W Grathwohl, RTQ Chen, D Duvenaud, JH Jacobsen
arXiv preprint arXiv:1811.00995, 2018
1442018
Residual flows for invertible generative modeling
RTQ Chen, J Behrmann, DK Duvenaud, JH Jacobsen
Advances in Neural Information Processing Systems, 9913-9923, 2019
642019
Latent ordinary differential equations for irregularly-sampled time series
Y Rubanova, RTQ Chen, DK Duvenaud
Advances in Neural Information Processing Systems, 5320-5330, 2019
572019
Latent odes for irregularly-sampled time series
Y Rubanova, RTQ Chen, D Duvenaud
arXiv preprint arXiv:1907.03907, 2019
412019
Scalable reversible generative models with free-form continuous dynamics
W Grathwohl, RTQ Chen, J Bettencourt, D Duvenaud
International Conference on Learning Representations, 2019
252019
Scalable gradients for stochastic differential equations
X Li, TKL Wong, RTQ Chen, D Duvenaud
arXiv preprint arXiv:2001.01328, 2020
242020
Neural networks with cheap differential operators
RTQ Chen, D Duvenaud
Advances in Neural Information Processing Systems, 9961-9971, 2019
92019
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
arXiv preprint arXiv:2004.00353, 2020
72020
Neural Ordinary Differential Equations. 2018
TQ Chen, Y Rubanova, J Bettencourt, D Duvenaud
URL http://arxiv. org/abs, 1806
51806
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
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
" 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
12020
Neural Spatio-Temporal Point Processes
RTQ Chen, B Amos, M Nickel
arXiv preprint arXiv:2011.04583, 2020
2020
Self-Tuning Stochastic Optimization with Curvature-Aware Gradient Filtering
RTQ Chen, D Choi, L Balles, D Duvenaud, P Hennig
arXiv preprint arXiv:2011.04803, 2020
2020
Learning Neural Event Functions for Ordinary Differential Equations
RTQ Chen, B Amos, M Nickel
arXiv preprint arXiv:2011.03902, 2020
2020
Deep kernel mean embeddings for generative modeling and feedforward style transfer
RTQ Chen
University of British Columbia, 2017
2017
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