Advances in deep learning over the last decade have led to a flurry of research in the
application of deep artificial neural networks to robotic systems, with at least 30 papers …

Abstract The Interdecadal Pacific Oscillation (IPO) influences multidecadal drought risk
across the Pacific, but there are no millennial‐length, high‐resolution IPO reconstructions for …

Malware classification is a difficult problem, to which machine learning methods have been
applied for decades. Yet progress has often been slow, in part due to a number of unique …

Abstract The Gesture Recognition Toolkit is a cross-platform open-source C++ library
designed to make real-time machine learning and gesture recognition more accessible for …

We present a neural network technique for the analysis and extrapolation of time-series data
called neural decomposition (ND). Units with a sinusoidal activation function are used to …

We present an open-source platform-independent C++ framework for machine learning and
computer vision research. The framework includes a wide range of standard machine …

We present a method for training a deep neural network containing sinusoidal activation
functions to fit to time-series data. Weights are initialized using a fast Fourier transform, then …

We present a method for training a deep neural network containing sinusoidal activation
functions to fit to time-series data. Weights are initialized using a fast Fourier transform, then …

The success of machine learning on a given task dependson, among other things, which
learning algorithm is selected and its associated hyperparameters. Selecting an appropriate …

We investigate a method for cooperative learning called weighted average model fusion that
enables neural networks to learn from the experiences of other networks, as well as from …