Well Log Generation via Ensemble Long Short‐Term Memory (EnLSTM) Network

Log-periodogram regression in asymmetric long memory

Filtered Log-periodogram Regression of long memory processes

Filtered log-periodogram regression estimation of the fractional differencing parameter d is considered. Asymptotic properties are derived and the effect of filtering on d̂ is investigated. It is shown that the estimator by Geweke and Porter-Hudak (1983) can be improved significantly using a simple family of filters. The essential improvement is based on a binary decision that is asymptotically ...

Hippocampal ensemble dynamics timestamp events in long-term memory

The capacity to remember temporal relationships between different events is essential to episodic memory, but little is currently known about its underlying mechanisms. We performed time-lapse imaging of thousands of neurons over weeks in the hippocampal CA1 of mice as they repeatedly visited two distinct environments. Longitudinal analysis exposed ongoing environment-independent evolution of e...

Neural Network Ensemble-Based Solar Power Generation Short-Term Forecasting

This paper presents the applicability of artificial neural networks for 24 hour ahead solar power generation forecasting of a 20 kW photovoltaic system, the developed forecasting is suitable for a reliable Microgrid energy management. In total four neural networks were proposed, namely: multi-layred perceptron, radial basis function, recurrent and a neural network ensemble consisting in ensembl...

Learning Sparse Markov Network Structure via Ensemble-of-Trees Models

Learning the sparse structure of a general Markov network is a hard computational problem. One of the main difficulties is the computation of the generally intractable partition function. To circumvent this difficulty, we propose to learn the network structure using an ensemble-oftrees (ET) model. The ET model was first introduced by Meilă and Jaakkola (2006), and it represents a multivariate d...