50 citations · 106 across the 10 of their papers we have counts for
12 papers
Label-free Monitoring of Self-Supervised Learning Progress
Isaac Xu, Scott Lowe, Thomas Trappenberg
Self-supervised learning (SSL) is an effective method for exploiting unlabelled data to learn a high-level embedding space that can be used for various downstream tasks. However, e…
LogAvgExp Provides a Principled and Performant Global Pooling Operator
Scott C. Lowe, Thomas Trappenberg, Sageev Oore
We seek to improve the pooling operation in neural networks, by applying a more theoretically justified operator. We demonstrate that LogSumExp provides a natural OR operator for l…
Logical Activation Functions: Logit-space equivalents of Probabilistic Boolean Operators
Scott C. Lowe, Robert Earle, Jason d'Eon +2
The choice of activation functions and their motivation is a long-standing issue within the neural network community. Neuronal representations within artificial neural networks are…
Multiplicative Decomposition of Heterogeneity in Mixtures of Continuous Distributions
Abraham Nunes, Martin Alda, Thomas Trappenberg
A system's heterogeneity (\textit{diversity}) is the effective size of its event space, and can be quantified using the Rényi family of indices (also known as Hill numbers in ecolo…
Representational Rényi heterogeneity
Abraham Nunes, Martin Alda, Timothy Bardouille +1
A discrete system's heterogeneity is measured by the Rényi heterogeneity family of indices (also known as Hill numbers or Hannah--Kay indices), whose units are {the numbers equival…
Skin cancer detection based on deep learning and entropy to detect outlier samples
Andre G. C. Pacheco, Abder-Rahman Ali, Thomas Trappenberg
We describe our methods that achieved the 3rd and 4th places in tasks 1 and 2, respectively, at ISIC challenge 2019. The goal of this challenge is to provide the diagnostic for ski…