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researcher

L. N. Darlow

3 papers here

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

author position
  • first author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CV1

identity via Semantic Scholar / OpenAlex

most citedLatent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks

9 citations · 9 across the 1 of their papers we have counts for

collaborators

3 papers

cs.LG2020★ 9 cited

Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks

Luke Darlow, Stanisław Jastrzębski, Amos Storkey

Collider bias is a harmful form of sample selection bias that neural networks are ill-equipped to handle. This bias manifests itself when the underlying causal signal is strongly c…

cs.CV2020

DHOG: Deep Hierarchical Object Grouping

Luke Nicholas Darlow, Amos Storkey

Recently, a number of competitive methods have tackled unsupervised representation learning by maximising the mutual information between the representations produced from augmentat…

cs.LG2020

What Information Does a ResNet Compress?

Luke Nicholas Darlow, Amos Storkey

The information bottleneck principle (Shwartz-Ziv & Tishby, 2017) suggests that SGD-based training of deep neural networks results in optimally compressed hidden layers, from an in…

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