Results 11 to 20 of about 2,032,964 (381)
Optoelectronic Reservoir Computing [PDF]
Scientific Reports, 2011 Reservoir computing is a recently introduced, highly efficient bio-inspired approach for processing time dependent data. The basic scheme of reservoir computing consists of a non linear recurrent dynamical system coupled to a single input layer and a ...
A Rodan +17 more
core +11 more sources
3D Multiclass Digital Core Models via microCT, SEM-EDS and Deep Learning [PDF]
E3S Web of Conferences, 2023 We describe an integrated methodology for constructing a 3D multiclass model of a rock sample, based on X-ray microtomography (microCT) and quantitative evaluation of minerals (QEMSCAN) by automated SEM-EDS (Scanning Electron Microscopy, Energy ...
Varfolomeev Igor +2 more
doaj +1 more source
Next generation reservoir computing [PDF]
Nature Communications, 2021 Reservoir computing is a best-in-class machine learning algorithm for processing information generated by dynamical systems using observed time-series data.
D. Gauthier +3 more
semanticscholar +1 more source
Comparing Centrifuge, Steady-State and Semi-Dynamic Methods for Relative Permeability and Capillary Pressure Determination: New Insights [PDF]
E3S Web of Conferences, 2023 Relative permeability and capillary pressure are essential parameters for understanding multiphase flow in porous media and scenarios of production in oil or gas reservoirs. There are several experimental methods for determining the relative permeability
Pairoys Fabrice +3 more
doaj +1 more source
Developments in Petroleum Science, 2021 fundamentals of rock properties, this guide covers critical field and lab tests, along with interpretations from actual drilling operations and worldwide case studies, including abnormal formation pressures from many major petroleum basins.
E. Fjær +4 more
semanticscholar +1 more source
All-ferroelectric implementation of reservoir computing
Nature Communications, 2023 Reservoir computing (RC) offers efficient temporal information processing with low training cost. All-ferroelectric implementation of RC is appealing because it can fully exploit the merits of ferroelectric memristors (e.g., good controllability ...
Zhiwei Chen +10 more
semanticscholar +1 more source
Nature Electronics, 2022 Reservoir computing offers a powerful neuromorphic computing architecture for spatiotemporal signal processing. To boost the power efficiency of the hardware implementations of reservoir computing systems, analogue devices and components—including ...
Yanan Zhong +11 more
semanticscholar +1 more source
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2021 We demonstrate that transformers obtain impressive performance even when some of the layers are randomly initialized and never updated. Inspired by old and well-established ideas in machine learning, we explore a variety of non-linear "reservoir" layers interspersed with regular transformer layers, and show improvements in wall-clock compute time until
Ari S. Morcos +5 more
openaire +3 more sources
Dynamic memristor-based reservoir computing for high-efficiency temporal signal processing
Nature Communications, 2021 Reservoir computing is a highly efficient network for processing temporal signals due to its low training cost compared to standard recurrent neural networks, and generating rich reservoir states is critical in the hardware implementation.
Yanan Zhong +5 more
semanticscholar +1 more source