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One-shot learning for solution operators of partial differential equations

Apr 06, 2021
Lu Lu, Haiyang He, Priya Kasimbeg, Rishikesh Ranade, Jay Pathak

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Physics-informed neural networks with hard constraints for inverse design

Feb 09, 2021
Lu Lu, Raphael Pestourie, Wenjie Yao, Zhicheng Wang, Francesc Verdugo, Steven G. Johnson

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Robots as Actors in a Film: No War, A Robot Story

Oct 27, 2019
Andreagiovanni Reina, Viktor Ioannou, Junjin Chen, Lu Lu, Charles Kent, James A. R. Marshall

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DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

Oct 08, 2019
Lu Lu, Pengzhan Jin, George Em Karniadakis

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Gated Multiple Feedback Network for Image Super-Resolution

Jul 10, 2019
Qilei Li, Zhen Li, Lu Lu, Gwanggil Jeon, Kai Liu, Xiaomin Yang

* Accepted to BMVC2019 

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DeepXDE: A deep learning library for solving differential equations

Jul 10, 2019
Lu Lu, Xuhui Meng, Zhiping Mao, George E. Karniadakis

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Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness

May 27, 2019
Pengzhan Jin, Lu Lu, Yifa Tang, George Em Karniadakis

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Dying ReLU and Initialization: Theory and Numerical Examples

Mar 15, 2019
Lu Lu, Yeonjong Shin, Yanhui Su, George Em Karniadakis

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Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems

Sep 21, 2018
Dongkun Zhang, Lu Lu, Ling Guo, George Em Karniadakis

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Collapse of Deep and Narrow Neural Nets

Aug 15, 2018
Lu Lu, Yanhui Su, George Em Karniadakis

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Robot Composite Learning and the Nunchaku Flipping Challenge

Sep 11, 2017
Leidi Zhao, Yiwen Zhao, Siddharth Patil, Dylan Davies, Cong Wang, Lu Lu, Bo Ouyang

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Multiform Adaptive Robot Skill Learning from Humans

Aug 17, 2017
Leidi Zhao, Raheem Lawhorn, Siddharth Patil, Steve Susanibar, Lu Lu, Cong Wang, Bo Ouyang

* Accepted to 2017 Dynamic Systems and Control Conference (DSCC), Tysons Corner, VA, October 11-13 

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