10 citations · 10 across the 3 of their papers we have counts for
4 papers
Neural Attentive Circuits
Nasim Rahaman, Martin Weiss, Francesco Locatello +5
Recent work has seen the development of general purpose neural architectures that can be trained to perform tasks across diverse data modalities. General purpose models typically m…
Non-Convergence and Limit Cycles in the Adam optimizer
Sebastian Bock, Martin Georg Weiß
One of the most popular training algorithms for deep neural networks is the Adaptive Moment Estimation (Adam) introduced by Kingma and Ba. Despite its success in many applications…
Local Convergence of Adaptive Gradient Descent Optimizers
Sebastian Bock, Martin Georg Weiß
Adaptive Moment Estimation (ADAM) is a very popular training algorithm for deep neural networks and belongs to the family of adaptive gradient descent optimizers. However to the be…
An improvement of the convergence proof of the ADAM-Optimizer
Sebastian Bock, Josef Goppold, Martin Weiß
A common way to train neural networks is the Backpropagation. This algorithm includes a gradient descent method, which needs an adaptive step size. In the area of neural networks,…