Abstract. This paper investigates the construction of a wide class of singlehidden layer neural networks (SLNNs) with or without tunable parameters in the hidden nodes. It is a cha...
Kang Li, Jian Xun Peng, Minrui Fei, Xiaoou Li, Wen...
Interference in neural networks occurs when learning in one area of the input space causes unlearning in another area. Networks that are less susceptible to interference are refer...
We present the theoretical results about the construction of confidence intervals for a nonlinear regression based on least squares estimation and using the linear Taylor expansio...
Artificial neural networks (ANNs) have shown great promise in modeling circuit parameters for computer aided design applications. Leakage currents, which depend on process paramete...
Janakiraman Viraraghavan, Bharadwaj Amrutur, V. Vi...
Background: Metabolic fluxes provide invaluable insight on the integrated response of a cell to environmental stimuli or genetic modifications. Current computational methods for e...
Ari Rantanen, Juho Rousu, Paula Jouhten, Nicola Za...