Deep Learning Beyond CS

作者 Felix A. Faber · Luke Hutchison · Bing Huang · Justin Gilmer · Samuel S. Schoenholz · George E. Dahl · Oriol Vinyals · Steven Kearnes · Patrick F. Riley · O. Anatole Von Lilienfeld

Neural Message Passing for Quantum Chemistry

2017

期刊 eprint arXiv:1704.01212 有全文

作者 Justin Gilmer · Samuel S. Schoenholz · Patrick F. Riley · Oriol Vinyals · George E. Dahl

Nonequilibrium thermodynamics of restricted Boltzmann machines

2017

期刊 Physical Review E 有全文

作者 Domingos S. P. Salazar

Overcoming the curse of dimensionality: Solving high-dimensional partial differential equations using deep learning

2017

期刊 eprint arXiv:1707.02568 有全文

作者 Jiequn Han · Arnulf Jentzen · Weinan E

Searching for turbulence models by artificial neural network

2017

期刊 Physical Review Fluids 有全文

作者 Masataka Gamahara · Yuji Hattori

Solving parametric PDE problems with artiﬁcial neural networks

2017

期刊 eprint arXiv:1707.03351 有全文

作者 Yuehaw Khoo · Jianfeng Lu · Lexing Ying

Stochastic Thermodynamics of Learning

2017

期刊 Physical Review Letters 有全文

作者 Sebastian Goldt · Udo Seifert

The quadratic Wasserstein metric for earthquake location

2017

期刊 arXiv 有全文

作者 Jing Chen · Yifan Chen · Hao Wu · Dinghui Yang

Accelerating Eulerian Fluid Simulation With Convolutional Networks

2016

期刊 eprint arXiv:1607.03597 有全文

作者 Jonathan Tompson · Kristofer Schlachter · Pablo Sprechmann · Ken Perlin

Bayesian Solution Uncertainty Quantification for Differential Equations

2016

期刊 Bayesian Analysis 有全文

作者 Oksana A. Chkrebtii · David A. Campbell · Ben Calderhead · Mark A. Girolami

Convolutional Neural Networks for Steady Flow Approximation

2016

会议 Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '16 有全文

作者 Xiaoxiao Guo · Wei Li · Francesco Iorio

Data-Driven Modeling and Dynamic Programming Applied to Batch Cooling Crystallization

2016

期刊 Industrial & Engineering Chemistry Research 有全文

作者 Daniel J. Griffin · Martha A. Grover · Yoshiaki Kawajiri · Ronald W. Rousseau

Machine-learning-assisted materials discovery using failed experiments

2016

期刊 Nature 有全文

作者 Paul Raccuglia · Katherine C. Elbert · Philip D. F. Adler · Casey Falk · Malia B. Wenny · Aurelio Mollo · Matthias Zeller · Sorelle A. Friedler · Joshua Schrier · Alexander J. Norquist

Molecular Graph Convolutions: Moving Beyond Fingerprints

2016

期刊 Journal of Computer-Aided Molecular Design 有全文

作者 Steven Kearnes · Kevin Mccloskey · Marc Berndl · Vijay Pande · Patrick Riley

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Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach

Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

Hidden physics models: Machine learning of nonlinear partial differential equations

Neural-network quantum state tomography

PDE-Net: Learning PDEs from Data

Planning chemical syntheses with deep neural networks and symbolic AI

A Flow Model of Neural Networks

Approximate solutions by artificial neural network of hybrid fuzzy differential equations

A Priori Assessment of Prediction Confidence for Data-Driven Turbulence Modeling

A publicly available crystallisation data set and its application in machine learning

A uniﬁed deep artiﬁcial neural network approach to partial diﬀerential equations in complex geometries

BEYOND FINITE LAYER NEURAL NETWORKS: BRIDGING DEEP ARCHITECTURES AND NUMERICAL DIFFERENTIAL EQUATIONS

Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge

DGM: A deep learning algorithm for solving partial differential equations

Machine-learned and codified synthesis parameters of oxide materials

Machine learning approximation algorithms for high-dimensional fully nonlinear partial diﬀerential equations and second-order backward stochastic diﬀerential equations

Machine learning prediction errors better than DFT accuracy

Neural Message Passing for Quantum Chemistry

Nonequilibrium thermodynamics of restricted Boltzmann machines

Overcoming the curse of dimensionality: Solving high-dimensional partial differential equations using deep learning

Searching for turbulence models by artificial neural network

Solving parametric PDE problems with artiﬁcial neural networks

Stochastic Thermodynamics of Learning

The quadratic Wasserstein metric for earthquake location

Accelerating Eulerian Fluid Simulation With Convolutional Networks

Bayesian Solution Uncertainty Quantification for Differential Equations

Convolutional Neural Networks for Steady Flow Approximation

Data-Driven Modeling and Dynamic Programming Applied to Batch Cooling Crystallization

Machine-learning-assisted materials discovery using failed experiments

Molecular Graph Convolutions: Moving Beyond Fingerprints