ODE $^2$ VAE: Deep generative second order ODEs with Bayesian neural networks

27 May 2019

Harri Lähdesmäki

Papers citing "ODE$^2$VAE: Deep generative second order ODEs with Bayesian neural networks"

21 / 21 papers shown

Title
Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers Kai Lagemann C. Lagemann Swarnava Mukherjee 44 2 0 21 Jun 2023
Hawkes Process Based on Controlled Differential Equations Minju Jo Seung-Uk Kook Noseong Park AI4TS 37 1 0 09 May 2023
VidStyleODE: Disentangled Video Editing via StyleGAN and NeuralODEs Moayed Haji-Ali Andrew Bond Tolga Birdal Duygu Ceylan Levent Karacan Erkut Erdem Aykut Erdem VGen DiffM 128 2 0 12 Apr 2023
Neural Langevin Dynamics: towards interpretable Neural Stochastic Differential Equations Simon Koop M. Peletier J. Portegies Vlado Menkovski DiffM 35 1 0 17 Nov 2022
Continuous PDE Dynamics Forecasting with Implicit Neural Representations Yuan Yin Matthieu Kirchmeyer Jean-Yves Franceschi A. Rakotomamonjy Patrick Gallinari AI4CE 25 49 0 29 Sep 2022
Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structures Zhilu Lai Wei Liu Xudong Jian Kiran Bacsa Limin Sun Eleni Chatzi AI4CE 26 22 0 16 Jul 2022
Variational Mixtures of ODEs for Inferring Cellular Gene Expression Dynamics Yichen Gu D. Blaauw Joshua D. Welch 21 14 0 09 Jul 2022
STONet: A Neural-Operator-Driven Spatio-temporal Network Haitao Lin Guojiang Zhao Lirong Wu Stan Z. Li AI4TS AI4CE 18 1 0 18 Apr 2022
Continual Learning of Multi-modal Dynamics with External Memory Abdullah Akgul Gözde B. Ünal M. Kandemir CLL 19 0 0 02 Mar 2022
Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations Paidamoyo Chapfuwa Sherri Rose Lawrence Carin Edward Meeds Ricardo Henao CML 22 1 0 25 Feb 2022
Imbedding Deep Neural Networks A. Corbett D. Kangin AI4TS 28 2 0 31 Jan 2022
Heavy Ball Neural Ordinary Differential Equations Hedi Xia Vai Suliafu H. Ji T. Nguyen Andrea L. Bertozzi Stanley J. Osher Bao Wang 38 56 0 10 Oct 2021
Efficient and Accurate Gradients for Neural SDEs Patrick Kidger James Foster Xuechen Li Terry Lyons DiffM 24 60 0 27 May 2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations Winnie Xu Ricky T. Q. Chen Xuechen Li David Duvenaud BDL UQCV 27 46 0 12 Feb 2021
On Second Order Behaviour in Augmented Neural ODEs Alexander Norcliffe Cristian Bodnar Ben Day Nikola Simidjievski Pietro Lio 36 90 0 12 Jun 2020
Stable Neural Flows Stefano Massaroli Michael Poli Michelangelo Bin Jinkyoo Park Atsushi Yamashita Hajime Asama 46 31 0 18 Mar 2020
Stochasticity in Neural ODEs: An Empirical Study V. Oganesyan Alexandra Volokhova Dmitry Vetrov BDL 30 20 0 22 Feb 2020
Stochastic Latent Residual Video Prediction Jean-Yves Franceschi E. Delasalles Mickaël Chen Sylvain Lamprier Patrick Gallinari VGen 26 159 0 21 Feb 2020
How to train your neural ODE: the world of Jacobian and kinetic regularization Chris Finlay J. Jacobsen L. Nurbekyan Adam M. Oberman 11 296 0 07 Feb 2020
Scalable Gradients for Stochastic Differential Equations Xuechen Li Ting-Kam Leonard Wong Ricky T. Q. Chen David Duvenaud 17 310 0 05 Jan 2020
Graph Neural Ordinary Differential Equations Michael Poli Stefano Massaroli Junyoung Park Atsushi Yamashita Hajime Asama Jinkyoo Park AI4CE 51 154 0 18 Nov 2019

ODE2^22VAE: Deep generative second order ODEs with Bayesian neural networks

Papers citing "ODE$^2$VAE: Deep generative second order ODEs with Bayesian neural networks"

ODE $^2$ VAE: Deep generative second order ODEs with Bayesian neural networks