Niv Giladi 个人学术档案 - 学术资源搜索

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Daniel SoudryAssociate Professor在 technion.ac.il 的电子邮件经过验证
Elad HofferPhD, Research @ Habana Labs在 habana.ai 的电子邮件经过验证
Torsten HoeflerProfessor of Computer Science at ETH Zurich在 inf.ethz.ch 的电子邮件经过验证
Tal Ben-NunLawrence Livermore National Laboratory在 llnl.gov 的电子邮件经过验证
Itay Hubara PhDSenior researchers at Intel-HabanaLabs在 habana.ai 的电子邮件经过验证
Dan LeviGeneral Motors R&D在 gm.com 的电子邮件经过验证
Ethan FetayaBar-Ilan University在 biu.ac.il 的电子邮件经过验证
Mor Shpigel NacsonPhD Student, Technion在 campus.technion.ac.il 的电子邮件经过验证
Zvika Ben-HaimGoogle在 google.com 的电子邮件经过验证
Sella NevoDirector of the Meselson Center, RAND在 rand.org 的电子邮件经过验证
Yossi MatiasGoogle在 tau.ac.il 的电子邮件经过验证
Kfir Yehuda LevyAssistant Professor at Technion - Israel Institute of Technology在 technion.ac.il 的电子邮件经过验证

Niv Giladi

在 campus.technion.ac.il 的电子邮件经过验证


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Augment your batch: Improving generalization through instance repetition E Hoffer, T Ben-Nun, I Hubara, N Giladi, T Hoefler, D Soudry Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020	318*	2020
Evaluating and calibrating uncertainty prediction in regression tasks D Levi, L Gispan, N Giladi, E Fetaya Sensors 22 (15), 5540, 2022	135	2022
Flood forecasting with machine learning models in an operational framework S Nevo, E Morin, A Gerzi Rosenthal, A Metzger, C Barshai, D Weitzner, ... Hydrology and Earth System Sciences 26 (15), 4013-4032, 2022	110	2022
At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks? N Giladi, MS Nacson, E Hoffer, D Soudry arXiv preprint arXiv:1909.12340, 2019	20	2019
Physics-Aware Downsampling with Deep Learning for Scalable Flood Modeling N Giladi, Z Ben-Haim, S Nevo, Y Matias, D Soudry Advances in Neural Information Processing Systems 34, 1378-1389, 2021	9	2021
DropCompute: simple and more robust distributed synchronous training via compute variance reduction N Giladi, S Gottlieb, A Karnieli, R Banner, E Hoffer, KY Levy, D Soudry Advances in Neural Information Processing Systems 36, 2024		2024
Google’s flood forecasting framework: connecting data, models, risks and people S Nevo, AG Rosenthal, A Metzger, D Weitzner, E Morin, G Elidan, ... AGU Fall Meeting 2020, 2020		2020

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