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Lior Wolf

Facebook AI Research and Tel Aviv University

53 papers hereh-index 6427k citations262 works total

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

author position
  • first author1
  • middle author12
  • last author40

Across the 53 of 53 papers where every author was matched, so the position is known.

fields
  • cs.LG22
  • cs.CV21
  • cs.SD6
  • cs.CR2
  • cs.CL1
  • eess.SP1
affiliations
  • Facebook AI Research and Tel Aviv University
Homepage
same name
  • Lior Wolf — 67 papers, h 38
  • Lior Wolf — 14 papers
  • Lior Wolf — 12 papers, h 8
  • Lior Wolf — 9 papers, h 3
  • Lior Wolf — 7 papers, h 3
  • Lior Wolf — 6 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172023
most citedLanguage Generation with Recurrent Generative Adversarial Networks without Pre-training

90 citations · 298 across the 31 of their papers we have counts for

collaborators
Showing 2017Show all

4 papers · 1 filter

cs.CV2017★ 1 cited

Compression Fractures Detection on CT

Amir Bar, Lior Wolf, Orna Bergman Amitai +2

The presence of a vertebral compression fracture is highly indicative of osteoporosis and represents the single most robust predictor for development of a second osteoporotic fract…

cs.CL2017★ 90 cited

Language Generation with Recurrent Generative Adversarial Networks without Pre-training

Ofir Press, Amir Bar, Ben Bogin +2

Generative Adversarial Networks (GANs) have shown great promise recently in image generation. Training GANs for language generation has proven to be more difficult, because of the…

cs.CV2017★ 55 cited

One-Sided Unsupervised Domain Mapping

Sagie Benaim, Lior Wolf

In unsupervised domain mapping, the learner is given two unmatched datasets A and B. The goal is to learn a mapping GAB​ that translates a sample in A to the analog sampl…

cs.LG2017★ 5 cited

A Theory of Output-Side Unsupervised Domain Adaptation

Tomer Galanti, Lior Wolf

When learning a mapping from an input space to an output space, the assumption that the sample distribution of the training data is the same as that of the test data is often viola…

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