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Mohamed Elhoseiny

4 papers here

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

author position
  • first author1
  • middle author2
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.CV1
same name
  • Mohamed Elhoseiny — 8 papers
  • Mohamed Elhoseiny — 7 papers, h 17
  • Mohamed Elhoseiny — 7 papers
  • Mohamed Elhoseiny — 4 papers
  • Mohamed Elhoseiny — 4 papers, h 7
  • Mohamed Elhoseiny — 1 paper

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

most citedEfficient Lifelong Learning with A-GEM

580 citations · 907 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2019

Uncertainty-guided Continual Learning with Bayesian Neural Networks

Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell +1

Continual learning aims to learn new tasks without forgetting previously learned ones. This is especially challenging when one cannot access data from previous tasks and when the m…

cs.LG2019★ 327 cited

On Tiny Episodic Memories in Continual Learning

Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny +4

In continual learning (CL), an agent learns from a stream of tasks leveraging prior experience to transfer knowledge to future tasks. It is an ideal framework to decrease the amoun…

cs.LG2019★ 580 cited

Efficient Lifelong Learning with A-GEM

Arslan Chaudhry, Marc'Aurelio Ranzato, Marcus Rohrbach +1

In lifelong learning, the learner is presented with a sequence of tasks, incrementally building a data-driven prior which may be leveraged to speed up learning of a new task. In th…

cs.CV2018

Exploring the Challenges towards Lifelong Fact Learning

Mohamed Elhoseiny, Francesca Babiloni, Rahaf Aljundi +3

So far life-long learning (LLL) has been studied in relatively small-scale and relatively artificial setups. Here, we introduce a new large-scale alternative. What makes the propos…

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