9 citations · 19 across the 7 of their papers we have counts for
5 papers · 1 filter
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…
Echofilter: A Deep Learning Segmentation Model Improves the Automation, Standardization, and Timeliness for Post-Processing Echosounder Data in Tidal Energy Streams
Scott C. Lowe, Louise P. McGarry, Jessica Douglas +4
Understanding the abundance and distribution of fish in tidal energy streams is important to assess risks presented by introducing tidal energy devices to the habitat. However tida…
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…
Program synthesis performance constrained by non-linear spatial relations in Synthetic Visual Reasoning Test
Lu Yihe, Scott C. Lowe, Penelope A. Lewis +1
Despite remarkable advances in automated visual recognition by machines, some visual tasks remain challenging for machines. Fleuret et al. (2011) introduced the Synthetic Visual Re…