TT-PINN: A Tensor-Compressed Neural PDE Solver for Edge Computing

Understanding the difficulty of training deep feedforward neural networks

Glorot, X. and Bengio, Y · 2010

Earlier work this paper cites.

Tensor-train decomposition

Oseledets, I. V · 2011

Earlier work this paper cites.

Tensor networks for big data analytics and large-scale optimization problems

Original

Cichocki, A · 2014

Earlier work this paper cites.

Adam: A method for stochastic optimization

Original

Kingma, D. P. and Ba, J · 2014

Earlier work this paper cites.

A practical introduction to tensor networks: Matrix product states and projected entangled pair states

Orús, R · 2014

Earlier work this paper cites.

Tensorizing neural networks

Novikov, A., Podoprikhin, D., Osokin, A., and Vetrov, D. P · 2015

Earlier work this paper cites.

Automatic differentiation in machine learning: a survey

Baydin, A. G., Pearlmutter, B. A., Radul, A. A., and Siskind, J. M · 2018

Cited alongside, same era.

Multi-fidelity physics-constrained neural network and its application in materials modeling

Liu, D. and Wang, Y · 2019

Cited alongside, same era.

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Raissi, M., Perdikaris, P., and Karniadakis, G. E · 2019

Cited alongside, same era.

Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations

Raissi, M., Yazdani, A., and Karniadakis, G. E · 2020

Cited alongside, same era.

AI for science

Stevens, R., Taylor, V., Nichols, J., Maccabe, A. B., Yelick, K., and Brown, D · 2020

Cited alongside, same era.

Deepreach: A deep learning approach to high-dimensional reachability

Bansal, S. and Tomlin, C. J · 2021

Later among the works it cites.

Bayesian tensorized neural networks with automatic rank selection

Hawkins, C. and Zhang, Z · 2021

Later among the works it cites.

Physics-informed neural networks with hard constraints for inverse design

Lu, L., Pestourie, R., Yao, W., Wang, Z., Verdugo, F., and Johnson, S. G · 2021

Later among the works it cites.

A neural network approach applied to multi-agent optimal control

Onken, D., Nurbekyan, L., Li, X., Fung, S. W., Osher, S., and Ruthotto, L · 2021

Later among the works it cites.

Towards compact neural networks via end-to-end training: A Bayesian tensor approach with automatic rank determination

Hawkins, C., Liu, X., and Zhang, Z · 2022

Closest in time.