Neural networks

By D. Signorini, J. Slattery, S. Dodds, V. Lane, P. Littlejohns. 1995

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In Model Architectures

Citations in the corpus

Variational Continual Learning (2017, background): “A general solution to continual learning would perform automatic model building that adds new structure to the existing model as new tasks are encountered (Rusu et al., 2016).”
A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017, background): “Among them, root mean squared error (RMSE) [Plutowski et al., 1996] and mean absolute error (MAE) are two scale-dependent measures, and mean absolute percentage error (MAPE) is a scale-dependent measure.”
Quantum-chemical insights from deep tensor neural networks (2016, methodology): “On the more fundamental side, the mathematical construction of the DTNN model provides statistically rigorous partitioning of extensive molecular properties into atomic contributions – a long-standing challenge for quantum-mechanical calculations of molecules.”
A New Representation of Skeleton Sequences for 3D Action Recognition (2017, methodology): “Recently, recurrent neural networks (RNNs) with Long-Short Term Memory (LSTM) neurons [7, 8] have also been used to model the spatial structure [4, 24, 36] or both the spatial and temporal information of skeleton sequences [16].”
Deep Learning on Lie Groups for Skeleton-Based Action Recognition (2016, background): “Already quite some works [46, 34, 2, 29, 33, 14, 15] have applied aspects of Lie group theory to deep neural networks.”
neuralnet: Training of Neural Networks (2010, background): “A detailed explanation is given in Rojas (1996). neuralnet provides the opportunity to switch between backpropagation, resilient backpropagation with (Riedmiller, 1994) or without weight backtracking (Riedmiller and Braun, 1993) and the modified globally convergent version by Anastasiadis et al.…”
WordICA—emergence of linguistic representations for words by independent component analysis (2010, methodology): “As a textbook account on SVD and PCA one can use, e.g., Haykin (1999).”