Vincent Le Guen

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All published works

Action	Title	Year	Authors
+	Complementing Brightness Constancy with Deep Networks for Optical Flow Prediction	2022	Vincent Le Guen Clément Rambour Nicolas Thome
+ PDF Chat	Augmenting physical models with deep networks for complex dynamics forecasting*	2021	Yuan Yin Vincent Le Guen Jérémie Donà Emmanuel de Bézenac Ibrahim Ayed Nicolas Thome Patrick Gallinari
+ PDF Chat	Augmenting physical models with deep networks for complex dynamics forecasting	2021	Yuan Yin Vincent Le Guen Jérémie Donà Ibrahim Ayed Emmanuel de Bézenac Nicolas Thome Patrick Gallinari
+	Disentangling Physical Dynamics From Unknown Factors for Unsupervised Video Prediction	2020	Vincent Le Guen Nicolas Thome

Common Coauthors

Coauthor	Papers Together
Nicolas Thome	4
Ibrahim Ayed	2
Emmanuel de Bézenac	2
Patrick Gallinari	2
Yuan Yin	2
Jérémie Donà	2
Clément Rambour	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Discovering governing equations from data by sparse identification of nonlinear dynamical systems	2016	Steven L. Brunton Joshua L. Proctor J. Nathan Kutz	3
+ PDF Chat	Deep learning for physical processes: incorporating prior scientific knowledge	2019	Emmanuel de Bézenac Arthur Pajot Patrick Gallinari	3
+ PDF Chat	Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics	2019	Yunbo Wang Jianjin Zhang Hongyu Zhu Mingsheng Long Jianmin Wang Philip S. Yu	2
+	A nonconvex set which has the unique nearest point property	1987	Gordon Johnson	2
+	Disentangling Physical Dynamics From Unknown Factors for Unsupervised Video Prediction	2020	Vincent Le Guen Nicolas Thome	2
+	Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces	2019	Philipp Becker Harit Pandya Gregor H. W. Gebhardt Cheng Zhao J. R. Taylor Gerhard Neumann	2
+	A strategy for operational implementation of 4D‐Var, using an incremental approach	1994	Philippe Courtier Jean‐Noël Thépaut A. Hollingsworth	2
+	PDE-Net: Learning PDEs from Data	2017	Zichao Long Yiping Lu Xianzhong Ma Bin Dong	2
+	Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting	2015	Xingjian Shi Zhourong Chen Hao Wang Dit‐Yan Yeung Wai Kin Wong Wang‐chun Woo	2
+	Neural ordinary differential equations	2018	Ricky T. Q. Chen Yulia Rubanova Jesse Bettencourt David Duvenaud	2
+ PDF Chat	A critical review of statistical calibration/prediction models handling data inconsistency and model inadequacy	2017	Pascal Pernot Fabien Cailliez	2
+	DGM: A deep learning algorithm for solving partial differential equations	2018	Justin Sirignano Konstantinos Spiliopoulos	2
+	PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning	2018	Yunbo Wang Zhifeng Gao Mingsheng Long Jianmin Wang Philip S. Yu	2
+	Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces	2019	Philipp Becker Harit Pandya Gregor H. W. Gebhardt Cheng Zhao C. James Taylor Gerhard Neumann	2
+ PDF Chat	Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning	2018	Anusha Nagabandi Gregory Kahn Ronald S. Fearing Sergey Levine	2
+ PDF Chat	FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks	2017	Eddy Ilg N. Michael Mayer Tonmoy Saikia Margret Keuper Alexey Dosovitskiy Thomas Brox	1
+ PDF Chat	Optical Flow Estimation Using a Spatial Pyramid Network	2017	Anurag Ranjan Michael J. Black	1
+	Spatio-temporal video autoencoder with differentiable memory	2015	Viorica Pătrăucean Ankur Handa Roberto Cipolla	1
+ PDF Chat	Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction	2017	Junbo Zhang Yu Zheng Dekang Qi	1
+	Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations	2017	Yiping Lu Aoxiao Zhong Quanzheng Li Bin Dong	1
+ PDF Chat	Data-driven discovery of partial differential equations	2017	Samuel Rudy Steven L. Brunton Joshua L. Proctor J. Nathan Kutz	1
+	A family of embedded Runge-Kutta formulae	1980	John R. Dormand P.J. Prince	1
+ PDF Chat	Data driven governing equations approximation using deep neural networks	2019	Tong Qin Kailiang Wu Dongbin Xiu	1
+	Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations	2017	Maziar Raissi Paris Perdikaris George Em Karniadakis	1
+	Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations	2018	Maziar Raissi	1
+	Neural Relational Inference for Interacting Systems	2018	Thomas Kipf Ethan Fetaya Kuan-Chieh Wang Max Welling Richard S. Zemel	1
+	Convolutional Neural Networks combined with Runge-Kutta Methods	2018	Mai Zhu Bo Chang Chong Fu	1
+	A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning	2017	M. Fraccaro Simon Kamronn Ulrich Paquet Ole Winther	1
+ PDF Chat	ContextVP: Fully Context-Aware Video Prediction	2018	Wonmin Byeon Qin Wang Rupesh K. Srivastava Petros Koumoutsakos	1
+	Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects	2018	Adam R. Kosiorek Hyunjik Kim Yee Whye Teh Ingmar Posner	1
+	Neural Jump Stochastic Differential Equations	2019	Junteng Jia Austin R. Benson	1
+	Generating Videos with Scene Dynamics	2016	Carl Vondrick Hamed Pirsiavash Antonio Torralba	1
+	Unsupervised Learning of Disentangled Representations from Video	2017	Emily Denton Vighnesh Birodkar	1
+ PDF Chat	DDFlow: Learning Optical Flow with Unlabeled Data Distillation	2019	Pengpeng Liu Irwin King Michael R. Lyu Xu Jia	1
+	Decomposing Motion and Content for Natural Video Sequence Prediction	2017	Ruben Villegas Shuicheng Yan Seunghoon Hong Xunyu Lin Honglak Lee	1
+	Backprop KF: Learning Discriminative Deterministic State Estimators	2016	Tuomas Haarnoja Anurag Ajay Sergey Levine Pieter Abbeel	1
+ PDF Chat	PDE-Net 2.0: Learning PDEs from data with a numeric-symbolic hybrid deep network	2019	Zichao Long Yiping Lu Bin Dong	1
+	Bilinear Residual Neural Network for the Identification and Forecasting of Geophysical Dynamics	2018	Ronan Fablet Said Ouala Cédric Herzet	1
+ PDF Chat	Video Frame Synthesis Using Deep Voxel Flow	2017	Ziwei Liu Raymond A. Yeh Xiaoou Tang Yiming Liu Aseem Agarwala	1
+ PDF Chat	SDC-Net: Video Prediction Using Spatially-Displaced Convolution	2018	Fitsum A. Reda Guilin Liu Kevin J. Shih Robert M. Kirby Jon Barker David Tarjan Andrew Tao Bryan Catanzaro	1
+	Learning Dynamical Systems from Partial Observations	2019	Ibrahim Ayed Emmanuel de Bézenac Arthur Pajot Julien Brajard Patrick Gallinari	1
+	Differentiable Physics-informed Graph Networks	2019	Sungyong Seo Yan Liu	1
+ PDF Chat	HybridNet: Classification and Reconstruction Cooperation for Semi-supervised Learning	2018	Thomas Robert Nicolas Thome Matthieu Cord	1
+	Hamiltonian Neural Networks	2019	Sam Greydanus Misko Dzamba Jason Yosinski	1
+	Generating Videos with Scene Dynamics	2016	Carl Vondrick Hamed Pirsiavash Antonio Torralba	1
+	Tackling Climate Change with Machine Learning	2019	David Rolnick Priya L. Donti Lynn H. Kaack Kelly Kochanski Alexandre Lacoste Kris Sankaran Andrew Slavin Ross Nikola Milojevic-Dupont Natasha Jaques Anna Waldman‐Brown	1
+ PDF Chat	Unsupervised Learning of Long-Term Motion Dynamics for Videos	2017	Zelun Luo Boya Peng De-An Huang Alexandre Alahi Li Fei-Fei	1
+	Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects	2018	Adam R. Kosiorek Hyunjik Kim Ingmar Posner Yee Whye Teh	1
+	Interaction Networks for Learning about Objects, Relations and Physics	2016	Peter Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu	1
+ PDF Chat	Flow-Grounded Spatial-Temporal Video Prediction from Still Images	2018	Yijun Li Fang Chen Shuicheng Yan Zhaowen Wang Xin Lu Ming–Hsuan Yang	1