1 citations · 1 across the 2 of their papers we have counts for
3 papers
Compact Recurrent Transformer with Persistent Memory
Edison Mucllari, Zachary Daniels, David Zhang +1
The Transformer architecture has shown significant success in many language processing and visual tasks. However, the method faces challenges in efficiently scaling to long sequenc…
Noise-Tolerant Coreset-Based Class Incremental Continual Learning
Edison Mucllari, Aswin Raghavan, Zachary Alan Daniels
Many applications of computer vision require the ability to adapt to novel data distributions after deployment. Adaptation requires algorithms capable of continual learning (CL). C…
Orthogonal Gated Recurrent Unit with Neumann-Cayley Transformation
Edison Mucllari, Vasily Zadorozhnyy, Cole Pospisil +2
In recent years, using orthogonal matrices has been shown to be a promising approach in improving Recurrent Neural Networks (RNNs) with training, stability, and convergence, partic…