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F. Vermet

13 papers hereh-index 13832 citations32 works total

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

author position
  • middle author3
  • last author10

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CV3
  • math.PR3
  • eess.SP1
  • q-fin.RM1
  • stat.ML1
same name
  • F. Vermet — 1 paper, h 2

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
20162026
most citedEvaluation of importance estimators in deep learning classifiers for Computed Tomography

2 citations · 3 across the 7 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2024

Oops, I Sampled it Again: Reinterpreting Confidence Intervals in Few-Shot Learning

Raphael Lafargue, Luke Smith, Franck Vermet +4

The predominant method for computing confidence intervals (CI) in few-shot learning (FSL) is based on sampling the tasks with replacement, i.e.\ allowing the same samples to appear…

cs.LG2020

Some Remarks on Replicated Simulated Annealing

Vincent Gripon, Matthias Löwe, Franck Vermet

Recently authors have introduced the idea of training discrete weights neural networks using a mix between classical simulated annealing and a replica ansatz known from the statist…

cs.LG2017

Improving Accuracy of Nonparametric Transfer Learning via Vector Segmentation

Vincent Gripon, Ghouthi B. Hacene, Matthias Löwe +1

Transfer learning using deep neural networks as feature extractors has become increasingly popular over the past few years. It allows to obtain state-of-the-art accuracy on dataset…

cs.LG2016

Associative Memories to Accelerate Approximate Nearest Neighbor Search

Vincent Gripon, Matthias Löwe, Franck Vermet

Nearest neighbor search is a very active field in machine learning for it appears in many application cases, including classification and object retrieval. In its canonical version…

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