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researcher

Karol Kurach

14 papers hereh-index 155.3k citations28 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author9
  • last author1

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.LG8
  • cs.CL2
  • cs.CV2
  • stat.ML2

identity via Semantic Scholar / OpenAlex

activity
20142019
most citedAdding Gradient Noise Improves Learning for Very Deep Networks

251 citations · 833 across the 13 of their papers we have counts for

collaborators
Showing stat.MLShow all

2 papers · 1 filter

stat.ML2017★ 77 cited

Are GANs Created Equal? A Large-Scale Study

Mario Lucic, Karol Kurach, Marcin Michalski +2

Generative adversarial networks (GAN) are a powerful subclass of generative models. Despite a very rich research activity leading to numerous interesting GAN algorithms, it is stil…

stat.ML2015★ 251 cited

Adding Gradient Noise Improves Learning for Very Deep Networks

Arvind Neelakantan, Luke Vilnis, Quoc V. Le +4

Deep feedforward and recurrent networks have achieved impressive results in many perception and language processing applications. This success is partially attributed to architectu…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.