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researcher

Aidan N. Gomez

University of Toronto

18 papers hereh-index 19184.2k citations34 works total

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

author position
  • first author3
  • middle author13
  • last author1

Across the 17 of 18 papers where every author was matched, so the position is known.

fields
  • cs.LG13
  • cs.CL3
  • cs.CV1
  • stat.ML1
affiliations
  • University of Toronto
Homepage

identity via Semantic Scholar / OpenAlex

activity
20172022
most citedOne Model To Learn Them All

258 citations · 1.1k across the 17 of their papers we have counts for

collaborators
Showing 2019Show all

3 papers · 1 filter

stat.ML2019★ 73 cited

A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks

Angelos Filos, Sebastian Farquhar, Aidan N. Gomez +6

Evaluation of Bayesian deep learning (BDL) methods is challenging. We often seek to evaluate the methods' robustness and scalability, assessing whether new tools give `better' unce…

cs.LG2019★ 30 cited

The Difficulty of Training Sparse Neural Networks

Utku Evci, Fabian Pedregosa, Aidan Gomez +1

We investigate the difficulties of training sparse neural networks and make new observations about optimization dynamics and the energy landscape within the sparse regime. Recent w…

cs.LG2019★ 74 cited

Learning Sparse Networks Using Targeted Dropout

Aidan N. Gomez, Ivan Zhang, Siddhartha Rao Kamalakara +4

Neural networks are easier to optimise when they have many more weights than are required for modelling the mapping from inputs to outputs. This suggests a two-stage learning proce…

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