This repository tracks a list of papers on machine learning applications in general relativity and, more generally, some PDE solvers and solution techniques that involve machine learning.
- 1911.11779 -- Enabling real-time multi-messenger astrophysics discoveries with deep learning
- 2105.06479 -- Advances in Machine and Deep Learning for Modeling and Real-time Detection of Multi-Messenger Sources
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1912.11073 -- Artificial neural network subgrid models of 2-D compressible magnetohydrodynamic turbulence
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1706.04702 -- Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations
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1711.06464 -- A unified deep artificial neural network approach to partial differential equations in complex geometries
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2001.06145 -- A Derivative-Free Method for Solving Elliptic Partial Differential Equations with Deep Neural Networks
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2003.00596 -- Overcoming the curse of dimensionality in the numerical approximation of high-dimensional semilinear elliptic partial differential equations
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1711.10561 -- Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations
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1711.10566 -- Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations
- 1711.03121 -- Deep Learning for Real-time Gravitational Wave Detection and Parameter Estimation: Results with Advanced LIGO Data
Daniel George, E. A. Huerta
CNN - 1909.05966 -- Learning Bayesian posteriors with neural networks for gravitational-wave inference
Alvin J. K. Chua, Michele Vallisneri
Perceptron - 1909.06296 -- Bayesian parameter estimation using conditional variational autoencoders for gravitational-wave astronomy
Hunter Gabbard, Chris Messenger, Ik Siong Heng, Francesco Tonolini, Roderick Murray-Smith
VAE - 2002.07656 -- Gravitational-wave parameter estimation with autoregressive neural network flows
Stephen R. Green, Christine Simpson, Jonathan Gair
NF - 2008.03312 -- Complete parameter inference for GW150914 using deep learning
Stephen R. Green, Jonathan Gair
NF - 2012.13101 -- Detection and Parameter Estimation of Gravitational Waves from Binary Neutron-Star Mergers in Real LIGO Data using Deep Learning
Plamen G. Krastev, Kiranjyot Gill, V. Ashley Villar, Edo Berger
CNN
- 1701.00008 -- Deep Neural Networks to Enable Real-time Multimessenger Astrophysics
Daniel George, E. A. Huerta
CNN - 1712.06041 -- Matching matched filtering with deep networks in gravitational-wave astronomy
Hunter Gabbard, Michael Williams, Fergus Hayes, Chris Messenger
CNN - 1904.08693 -- Convolutional neural networks: a magic bullet for gravitational-wave detection?
Timothy D. Gebhard, Niki Kilbertus, Ian Harry, Bernhard Schölkopf
CNN - 1909.13442 -- Gravitational wave signal recognition of O1 data by deep learning
He Wang, Zhoujian Cao, Xiaolin Liu, Shichao Wu, Jian-Yang Zhu
CNN - 1908.03151 -- Real-Time Detection of Gravitational Waves from Binary Neutron Stars using Artificial Neural Networks
Plamen G. Krastev
CNN - 2007.04176 -- Detection of Gravitational Waves Using Bayesian Neural Networks
Yu-Chiung Lin, Jiun-Huei Proty Wu
CNN/LSTM - 2009.04088 -- Deep learning for gravitational-wave data analysis: A resampling white-box approach
Manuel D. Morales, Javier M. Antelis, Claudia Moreno, Alexander I. Nesterov
CNN - 2011.04418 -- Improved deep learning techniques in gravitational-wave data analysis
Heming Xia, Lijing Shao, Junjie Zhao, Zhoujian Cao
CNN
- 1901.00869 -- Gravitational Wave Denoising of Binary Black Hole Mergers with Deep Learning
Wei Wei, E. A. Huerta
CNN (WaveNet) - 2012.03963 -- Deep Learning with Quantized Neural Networks for Gravitational Wave Forecasting of Eccentric Compact Binary Coalescence
Wei Wei, E. A. Huerta, Mengshen Yun, Nicholas Loutrel, Roland Haas, Volodymyr Kindratenko
ResNet
- 1312.6114
- 1401.4082
- 1505.05770
- 1606.04934
- 1705.07057