Fetching the paper…
Reading the bibliography…
Computer simulations are invaluable tools for scientific discovery.
Robust estimation of a location parameter
Peter J Huber · 1992
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
Earlier work this paper cites.
Edge localized modes (elms)
Hartmut Zohm · 1996
Earlier work this paper cites.
A finite-volume, incompressible navier stokes model for studies of the ocean on parallel computers
John Marshall, Alistair Adcroft, Chris Hill, Lev Perelman, and Curt Heisey · 1997
Earlier work this paper cites.
Theoretical model of x-ray scattering as a dense matter probe
G Gregori, Siegfried H Glenzer, W Rozmus, RW Lee, and OL Landen · 2003
Earlier work this paper cites.
Computational high-throughput screening of electrocatalytic materials for hydrogen evolution
Jeff Greeley, Thomas F Jaramillo, Jacob Bonde, IB Chorkendorff, and Jens K Nørskov · 2006
Earlier work this paper cites.
A computational framework for simulation of biogeochemical tracers in the ocean
Samar Khatiwala · 2007
Earlier work this paper cites.
Natural evolution strategies
Daan Wierstra, Tom Schaul, Jan Peters, and Juergen Schmidhuber · 2008
Earlier work this paper cites.
Ultrafast x-ray thomson scattering of shock-compressed matter
Andrea L Kritcher, Paul Neumayer, John Castor, Tilo Döppner, Roger W Falcone, Otto L Landen, Hae Ja Lee, Richard W Lee, Edward C Morse, Andrew Ng, et al · 2008
Earlier work this paper cites.
X-ray thomson-scattering measurements of density and temperature in shock-compressed beryllium
HJ Lee, P Neumayer, J Castor, T Döppner, RW Falcone, C Fortmann, BA Hammel, AL Kritcher, OL Landen, RW Lee, et al · 2009
Earlier work this paper cites.
Ensemble samplers with affine invariance
Jonathan Goodman and Jonathan Weare · 2010
Earlier work this paper cites.
Scikit-learn: Machine learning in python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al · 2011
Earlier work this paper cites.
Galaxy clustering in the newfirm medium band survey: the relationship between stellar mass and dark matter halo mass at 1¡ z¡ 2
David A Wake, Katherine E Whitaker, Ivo Labbé, Pieter G Van Dokkum, Marijn Franx, Ryan Quadri, Gabriel Brammer, Mariska Kriek, Britt F Lundgren, Danilo Marchesini, et al · 2011
Earlier work this paper cites.
Fast and accurate modeling of molecular atomization energies with machine learning
Matthias Rupp, Alexandre Tkatchenko, Klaus-Robert Müller, and O Anatole Von Lilienfeld · 2012
Earlier work this paper cites.
Seismic tomography of shatsky rise by adaptive importance sampling
J Korenaga and WW Sager · 2012
Earlier work this paper cites.
Hot-spot mix in ignition-scale inertial confinement fusion targets
SP Regan, R Epstein, BA Hammel, LJ Suter, HA Scott, MA Barrios, DK Bradley, DA Callahan, C Cerjan, GW Collins, et al · 2013
Earlier work this paper cites.
A gaussian process surrogate model assisted evolutionary algorithm for medium scale expensive optimization problems
Bo Liu, Qingfu Zhang, and Georges GE Gielen · 2013
Earlier work this paper cites.
Novel free-boundary equilibrium and transport solver with theory-based models and its validation against asdex upgrade current ramp scenarios
E Fable, C Angioni, FJ Casson, D Told, AA Ivanov, F Jenko, RM McDermott, S Yu Medvedev, GV Pereverzev, F Ryter, et al · 2013
Cited alongside, same era.
Particle transport analysis of the density build-up after the l–h transition in asdex upgrade
M Willensdorfer, E Fable, E Wolfrum, Leena Aho-Mantila, F Aumayr, R Fischer, F Reimold, F Ryter, et al · 2013
Cited alongside, same era.
Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
Cited alongside, same era.
Cosmic emulation: fast predictions for the galaxy power spectrum
Juliana Kwan, Katrin Heitmann, Salman Habib, Nikhil Padmanabhan, Earl Lawrence, Hal Finkel, Nicholas Frontiere, and Adrian Pope · 2015
Cited alongside, same era.
Taking the human out of the loop: A review of bayesian optimization
Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P Adams, and Nando De Freitas · 2015
Calibrating a global three-dimensional biogeochemical ocean model (mops-1.0)
Iris Kriest, Volkmar Sauerland, Samar Khatiwala, Anand Srivastav, and Andreas Oschlies · 2017
Later among the works it cites.
Beam-ion acceleration during edge localized modes in the asdex upgrade tokamak
J Galdon-Quiroga, Manuel Garcia-Munoz, KG McClements, M Nocente, M Hoelzl, AS Jacobsen, F Orain, JF Rivero-Rodriguez, Mirko Salewski, L Sanchis-Sanchez, et al · 2018
Later among the works it cites.
Deep image prior
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2018
Later among the works it cites.
Efficient neural architecture search via parameter sharing
Hieu Pham, Melody Y Guan, Barret Zoph, Quoc V Le, and Jeff Dean · 2018
Later among the works it cites.
Proxylessnas: Direct neural architecture search on target task and hardware
Han Cai, Ligeng Zhu, and Song Han · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Mops-1.0: modelling the regulation of the global oceanic nitrogen budget by marine biogeochemical processes
Iris Kriest and Andreas Oschlies · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
The cma evolution strategy: A tutorial
Nikolaus Hansen · 2016
Cited alongside, same era.
The galaxy–halo connection in the video survey at 0.5¡ z¡ 1.7
PW Hatfield, SN Lindsay, MJ Jarvis, B Häußler, M Vaccari, and A Verma · 2016
Cited alongside, same era.
Cma-es for hyperparameter optimization of deep neural networks
Ilya Loshchilov and Frank Hutter · 2016
Cited alongside, same era.
Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani · 2016
Cited alongside, same era.
Zonal flow generation in inertial confinement fusion implosions
JL Peterson, KD Humbird, JE Field, ST Brandon, SH Langer, RC Nora, BK Spears, and PT Springer · 2017
Cited alongside, same era.
Laboratory evidence of dynamo amplification of magnetic fields in a turbulent plasma
P Tzeferacos, A Rigby, AFA Bott, AR Bell, R Bingham, A Casner, F Cattaneo, EM Churazov, J Emig, F Fiuza, et al · 2018
Later among the works it cites.
Umap: Uniform manifold approximation and projection for dimension reduction
Leland McInnes, John Healy, and James Melville · 2018
Later among the works it cites.
Machine learning-based longitudinal phase space prediction of particle accelerators
C Emma, A Edelen, MJ Hogan, B O’Shea, G White, and V Yakimenko · 2018
Later among the works it cites.
Ion heat transport dynamics during edge localized mode cycles at asdex upgrade
E Viezzer, M Cavedon, E Fable, FM Laggner, RM McDermott, J Galdon-Quiroga, MG Dunne, A Kappatou, C Angioni, P Cano-Megias, et al · 2018
Later among the works it cites.
samarkhatiwala/tmm: Version 2.0 of the transport matrix method software, May 2018
samarkhatiwala · 2018
Later among the works it cites.
The global aerosol-climate model echam6. 3-ham2. 3-part 1: Aerosol evaluation
Ina Tegen, David Neubauer, Sylvaine Ferrachat, Siegenthaler-Le Drian, Isabelle Bey, Nick Schutgens, Philip Stier, Duncan Watson-Parris, Tanja Stanelle, Hauke Schmidt, et al · 2019
Later among the works it cites.
Cycle consistent surrogate for inertial confinement fusion
Rushil Anirudh, Peer-Timo Bremer, Jayaraman Jayaraman Thiagrarjan, and USDOE National Nuclear Security Administration · 2019
Later among the works it cites.
Inverse problem instabilities in large-scale modeling of matter in extreme conditions
MF Kasim, TP Galligan, J Topp-Mugglestone, G Gregori, and SM Vinko · 2019
Later among the works it cites.
The convergence rate of neural networks for learned functions of different frequencies
Basri Ronen, David Jacobs, Yoni Kasten, and Shira Kritchman · 2019
Later among the works it cites.
Efficient parameter sampling for neural network construction
Drimik Roy Chowdhury and Muhammad Firmansyah Kasim · 2019
Later among the works it cites.
Predicting disruptive instabilities in controlled fusion plasmas through deep learning
Julian Kates-Harbeck, Alexey Svyatkovskiy, and William Tang · 2019
Later among the works it cites.
Improved surrogates in inertial confinement fusion with manifold and cycle consistencies
Rushil Anirudh, Jayaraman J Thiagarajan, Peer-Timo Bremer, and Brian K Spears · 2020
Closest in time.