Fetching the paper…
Reading the bibliography…
Reproducibility of a deep-learning fully convolutional neural network is evaluated by training several times the same network on identical conditions (database, hyperparameters, hardware) with non-deterministic Graphics Processings Unit (GPU) operations.
Reproducible research in computational science
R. D. Peng · 2011
Earlier work this paper cites.
Precision & performance: Floating point and IEEE 754 compliance for NVIDIA GPUs
Nathan Whitehead and Alex Fit-Florea · 2011
Earlier work this paper cites.
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
Emily L Denton, Soumith Chintala, Arthur Szlam, and Rob Fergus · 2015
Earlier work this paper cites.
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Earlier work this paper cites.
Reproducible and accurate matrix multiplication
Roman Iakymchuk, David Defour, Sylvain Collange, and Stef Graillat · 2015
Earlier work this paper cites.
Estimation of numerical reproducibility on CPU and GPU
Fabienne Jézéquel, Jean-Luc Lamotte, and Issam Saïd · 2015
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
D.P. Kingma and L.J. Ba · 2015
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
The Lattice Boltzmann Method: Principles and Practice
T. Krüger, H. Kusumaatmaja, A. Kuzmin, O. Shardt, G. Silva, and E.M. Viggen · 2016
Earlier work this paper cites.
Deep multi-scale video prediction beyond mean square error
Michaël Mathieu, Camille Couprie, and Yann LeCun · 2016
Earlier work this paper cites.
Accelerating Eulerian fluid simulation with convolutional networks
Jonathan Tompson, Kristofer Schlachter, Pablo Sprechmann, and Ken Perlin · 2017
Earlier work this paper cites.
A unified deep artificial neural network approach to partial differential equations in complex geometries
Jens Berg and Kaj Nyström · 2018
Earlier work this paper cites.
Reproducibility in Scientific Computing
Peter Ivie and Douglas Thain · 2018
Cited alongside, same era.
Mixed precision training
Paulius Micikevicius, Sharan Narang, Jonah Alben, Gregory Diamos, Erich Elsen, David Garcia, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, and Hao Wu · 2018
Cited alongside, same era.
The impact of nondeterminism on reproducibility in deep reinforcement learning
Prabhat Nagarajan, Garrett Warnell, and Peter Stone · 2018
Cited alongside, same era.
A study on convolution using half-precision floating-point numbers on GPU for radio astronomy deconvolution
Mickael Seznec, Nicolas Gac, Andre Ferrari, and Francois Orieux · 2018
Cited alongside, same era.
DGM: A deep learning algorithm for solving partial differential equations
Justin Sirignano and Konstantinos Spiliopoulos · 2018
Cited alongside, same era.
Approximating the solution to wave propagation using deep neural networks
Machine learning for fluid mechanics
Steven L. Brunton, Bernd R. Noack, and Petros Koumoutsakos · 2020
Later among the works it cites.
Deterministic atomic buffering
Yuan Hsi Chou, Christopher Ng, Shaylin Cattell, Jeremy Intan, Matthew D. Sinclair, Joseph Devietti, Timothy G. Rogers, and Tor M. Aamodt · 2020
Later among the works it cites.
Comparing recurrent and convolutional neural networks for predicting wave propagation
Stathi Fotiadis, Eduardo Pignatelli, Mario Lino Valencia, Chris Cantwell, Amos Storkey, and Anil A. Bharath · 2020
Later among the works it cites.
Palabos: Parallel Lattice Boltzmann Solver
Jonas Latt, Orestis Malaspinas, Dimitrios Kontaxakis, Andrea Parmigiani, Daniel Lagrava, Federico Brogi, Mohamed Ben Belgacem, Yann Thorimbert, Sébastien Leclaire, Sha Li, Francesco Marson, Jonathan Lemus, Christos Kotsalos, Raphaël Conradin, Christophe Coreixas, Rémy Petkantchin, Franck Raynaud, Joël Beny, and Bastien Chopard · 2020
Later among the works it cites.
Random Search and Reproducibility for Neural Architecture Search
Liam Li and Ameet Talwalkar · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Wilhelm Sorteberg, Stef Garasto, Alison Pouplin, Chris Cantwell, and Anil Anthony Bharath · 2018
Cited alongside, same era.
Performance evaluation of cuDNN convolution algorithms on NVIDIA volta GPUs
Marc Jorda, Pedro Valero-Lara, and Antonio J. Pena · 2019
Cited alongside, same era.
Data-driven prediction of unsteady flow over a circular cylinder using deep learning
Sangseung Lee and Donghyun You · 2019
Cited alongside, same era.
Mechanisms of a convolutional neural network for learning three-dimensional unsteady wake flow
Sangseung Lee and Donghyun You · 2019
Cited alongside, same era.
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
Cited alongside, same era.
Predicting the Propagation of Acoustic Waves using Deep Convolutional Neural Networks
Antonio Alguacil, Michaël Bauerheim, Marc C. Jacob, and Stephane Moreau · 2020
Cited alongside, same era.
PPINN: Parareal physics-informed neural network for time-dependent PDEs
Xuhui Meng, Zhen Li, Dongkun Zhang, and George Em Karniadakis · 2020
Later among the works it cites.
Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d’Alché Buc, Emily B. Fox, and Hugo Larochelle · 2020
Later among the works it cites.
Variability and reproducibility in deep learning for medical image segmentation
Félix Renard, Soulaimane Guedria, Noel De Palma, and Nicolas Vuillerme · 2020
Later among the works it cites.
CUDA Toolkit Documentation v11.1.0: 2.1.4. Results reproducibility
NVIDIA Corporation · 2021
Closest in time.
cuDNN Developer Guide: Chapter 8. Reproducibility (determinism)
NVIDIA Corporation · 2021
Closest in time.
PyTorch documentation
Torch contributors · 2021
Closest in time.