◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Laetitia Shao

2 papers here

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

author position
  • first author1

Across the 1 of 2 papers where every author was matched, so the position is known.

fields
  • cs.LG2

identity via Semantic Scholar / OpenAlex

collaborators

2 papers

cs.LG2020

Neighbourhood Distillation: On the benefits of non end-to-end distillation

Laëtitia Shao, Max Moroz, Elad Eban +1

End-to-end training with back propagation is the standard method for training deep neural networks. However, as networks become deeper and bigger, end-to-end training becomes more…

cs.LG2020

Understanding Classifier Mistakes with Generative Models

Laëtitia Shao, Yang Song, Stefano Ermon

Although deep neural networks are effective on supervised learning tasks, they have been shown to be brittle. They are prone to overfitting on their training distribution and are e…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.