Fetching the paper…
Reading the bibliography…
Weather and climate simulations produce petabytes of high-resolution data that are later analyzed by researchers in order to understand climate change or severe weather.
Simfs: A simulation data virtualizing file system interface
Salvatore Di Girolamo, Pirmin Schmid, Thomas Schulthess, and Torsten Hoefler · 1902
Earlier work this paper cites.
Scrambling sobol’and niederreiter–xing points
Art B Owen · 1998
Earlier work this paper cites.
Stochastic learning
Léon Bottou · 2004
Earlier work this paper cites.
The new ccsds image compression recommendation
Pen-Shu Yeh, Philippe Armbruster, Aaron Kiely, Bart Masschelein, Gilles Moury, Christoph Schaefer, and Carole Thiebaut · 2005
Earlier work this paper cites.
Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien N. P. Martel, Alexander W. Bergman, David B. Lindell, and Gordon Wetzstein · 2006
Earlier work this paper cites.
Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T. Barron, and Ren Ng · 2006
Earlier work this paper cites.
Compression of multidimensional images using jpeg2000
H.G. Lalgudi, Ali Bilgin, Michael Marcellin, and Mariappan Nadar · 2008
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Fixed-rate compressed floating-point arrays
Peter Lindstrom · 2014
Earlier work this paper cites.
The community earth system model (cesm) large ensemble project: A community resource for studying climate change in the presence of internal climate variability
Jennifer E Kay, Clara Deser, A Phillips, A Mai, Cecile Hannay, Gary Strand, Julie Michelle Arblaster, SC Bates, Gokhan Danabasoglu, James Edwards, et al · 2015
Earlier work this paper cites.
The evolution of the ecmwf hybrid data assimilation system
Massimo Bonavita, Elias Hólm, Lars Isaksen, and Mike Fisher · 2016
Earlier work this paper cites.
Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
Earlier work this paper cites.
Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
Cited alongside, same era.
Reptile: a scalable metalearning algorithm
Alex Nichol and John Schulman · 2018
Cited alongside, same era.
Tthresh: Tensor compression for multidimensional visual data
Rafael Ballester-Ripoll, Peter Lindstrom, and Renato Pajarola · 2019
Cited alongside, same era.
Reflecting on the goal and baseline for exascale computing: a roadmap based on weather and climate simulations
Thomas Schulthess, P. Bauer, Oliver Fuhrer, Torsten Hoefler, C. Schaer, and N. Wedi · 2019
Cited alongside, same era.
Kilometer-scale climate models: Prospects and challenges
Christoph Schär, Oliver Fuhrer, Andrea Arteaga, Nikolina Ban, Christophe Charpilloz, Salvatore Di Girolamo, Laureline Hentgen, Torsten Hoefler, Xavier Lapillonne, David Leutwyler, Katherine Osterried, Davide Panosetti, Stefan Rüdisühli, Linda Schlemmer, Thomas Schulthess, Michael Sprenger, Stefano Ubbiali, and Heini Wernli · 2019
A survey of quantization methods for efficient neural network inference, 2021
Amir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael W. Mahoney, and Kurt Keutzer · 2021
Later among the works it cites.
Deep learning for post-processing ensemble weather forecasts
Peter Grönquist, Chengyuan Yao, Tal Ben-Nun, Nikoli Dryden, Peter Dueben, Shigang Li, and Torsten Hoefler · 2021
Later among the works it cites.
Torsten Hoefler, Dan Alistarh, Tal Ben-Nun, Nikoli Dryden, and Alexandra Peste · 2021
Later among the works it cites.
Compressive neural representations of volumetric scalar fields
Yuzhe Lu, Kairong Jiang, Joshua A. Levine, and Matthew Berger · 2021
Later among the works it cites.
Nerf: Representing scenes as neural radiance fields for view synthesis
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
The era5 global reanalysis
Hans Hersbach, Bill Bell, Paul Berrisford, Shoji Hirahara, András Horányi, Joaquín Muñoz-Sabater, Julien Nicolas, Carole Peubey, Raluca Radu, Dinand Schepers, et al · 2020
Cited alongside, same era.
Weatherbench: a benchmark data set for data-driven weather forecasting
Stephan Rasp, Peter D Dueben, Sebastian Scher, Jonathan A Weyn, Soukayna Mouatadid, and Nils Thuerey · 2020
Cited alongside, same era.
Sdrbench: Scientific data reduction benchmark for lossy compressors
Kai Zhao, Sheng Di, Xin Lian, Sihuan Li, Dingwen Tao, Julie Bessac, Zizhong Chen, and Franck Cappello · 2020
Cited alongside, same era.
Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields
Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan · 2021
Cited alongside, same era.
Nerv: Neural representations for videos
Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser Nam Lim, and Abhinav Shrivastava · 2021
Cited alongside, same era.
Clairvoyant Prefetching for Distributed Machine Learning I/O
Nikoli Dryden, Roman Böhringer, Tal Ben-Nun, and Torsten Hoefler · 2021
Cited alongside, same era.
Coin: Compression with implicit neural representations
Emilien Dupont, Adam Goliński, Milad Alizadeh, Yee Whye Teh, and Arnaud Doucet · 2021
Cited alongside, same era.
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2021
Later among the works it cites.
Ens-10: A dataset for post-processing ensemble weather forecast
Saleh Ashkboos, Langwen Huang, Nikoli Dryden, Tal Ben-Nun, Peter Dueben, Lukas Gianinazzi, Luca Kummer, and Torsten Hoefler · 2022
Closest in time.
Coin++: Neural compression across modalities
Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Y Whye Teh, and Arnaud Doucet · 2022
Closest in time.
Sz3: A modular framework for composing prediction-based error-bounded lossy compressors
Xin Liang, Kai Zhao, Sheng Di, Sihuan Li, Robert Underwood, Ali M Gok, Jiannan Tian, Junjing Deng, Jon C Calhoun, Dingwen Tao, et al · 2022
Closest in time.
Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
Closest in time.
Neural implicit flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data
Shaowu Pan, Steven L. Brunton, and J. Nathan Kutz · 2022
Closest in time.
Meta-learning sparse compression networks
Jonathan Richard Schwarz and Yee Whye Teh · 2022
Closest in time.