no code implementations • 2 Nov 2021 • Scott C. Lowe, Thomas Trappenberg, Sageev Oore
We seek to improve the pooling operation in neural networks, by applying a more theoretically justified operator.
no code implementations • 22 Oct 2021 • Scott C. Lowe, Robert Earle, Jason d'Eon, Thomas Trappenberg, Sageev Oore
Consequently, we construct efficient approximations named $\text{AND}_\text{AIL}$ (the AND operator Approximate for Independent Logits), $\text{OR}_\text{AIL}$, and $\text{XNOR}_\text{AIL}$, which utilize only comparison and addition operations, have well-behaved gradients, and can be deployed as activation functions in neural networks.
1 code implementation • 10 Dec 2019 • Abraham Nunes, Martin Alda, Timothy Bardouille, Thomas Trappenberg
Unfortunately, numbers equivalent heterogeneity measures for non-categorical data require {a priori} (A) categorical partitioning and (B) pairwise distance measurement on the observable data space, thereby precluding application to problems with ill-defined categories or where semantically relevant features must be learned as abstractions from some data.
no code implementations • 10 Sep 2019 • 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.
no code implementations • ICLR 2018 • Michael Traynor, Thomas Trappenberg
This work introduces a simple network for producing character aware word embeddings.
no code implementations • 20 Dec 2014 • Thomas Trappenberg, Paul Hollensen, Pitoyo Hartono
In this study we want to connect our previously proposed context-relevant topographical maps with the deep learning community.