This is the dataset of "In materia reservoir computing with a fully memristive architecture based on self-organizing nanowire networks"Part of this work was supported by the European project MEMQuD, code 20FUN06, funder ID: 10.13039/100014132. This project (EMPIR 20FUN06 MEMQuD) has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme
The quest for novel computing architectures is currently driven by (1) machine learning applications...
Dataset supporting the publication "Reservoir computing using back-end-of-line SiC-based memris...
By 2020, there will be 50 to 100 billion devices connected to the Internet. Two domains of hot resea...
Neuromorphic computing aims at the realization of intelligent systems able to process information si...
This is the dataset of "Connectome of memristive nanowire networks through graph theory"Part of this...
The past decade has seen a sharp rise in the development and manufacture of different hardware frame...
The hardware implementation of the reservoir computing paradigm represents a key aspect for taking i...
We present simulation results based on a model of self–assembled nanowire networks with memristive j...
Neuromorphic engineering is the research field dedicated to the study and design of brain-inspired h...
This is the dataset of "Grid-graph modeling of emergent neuromorphic dynamics and heterosynaptic pla...
Emerging memcapacitive nanoscale devices have the potential to perform computations in new ways. In ...
Self-assembled memristive nanonetworks composed of many interacting nano objects have been recently ...
Dataset for the thesis 'Memristor-based Spiking Neural Networks'. This dataset contains two ...
Unconventional computing explores multi-scale platforms connecting molecular-scale devices into netw...
Networks of nanowires are currently being explored for a range of applications in brain-like (or neu...
The quest for novel computing architectures is currently driven by (1) machine learning applications...
Dataset supporting the publication "Reservoir computing using back-end-of-line SiC-based memris...
By 2020, there will be 50 to 100 billion devices connected to the Internet. Two domains of hot resea...
Neuromorphic computing aims at the realization of intelligent systems able to process information si...
This is the dataset of "Connectome of memristive nanowire networks through graph theory"Part of this...
The past decade has seen a sharp rise in the development and manufacture of different hardware frame...
The hardware implementation of the reservoir computing paradigm represents a key aspect for taking i...
We present simulation results based on a model of self–assembled nanowire networks with memristive j...
Neuromorphic engineering is the research field dedicated to the study and design of brain-inspired h...
This is the dataset of "Grid-graph modeling of emergent neuromorphic dynamics and heterosynaptic pla...
Emerging memcapacitive nanoscale devices have the potential to perform computations in new ways. In ...
Self-assembled memristive nanonetworks composed of many interacting nano objects have been recently ...
Dataset for the thesis 'Memristor-based Spiking Neural Networks'. This dataset contains two ...
Unconventional computing explores multi-scale platforms connecting molecular-scale devices into netw...
Networks of nanowires are currently being explored for a range of applications in brain-like (or neu...
The quest for novel computing architectures is currently driven by (1) machine learning applications...
Dataset supporting the publication "Reservoir computing using back-end-of-line SiC-based memris...
By 2020, there will be 50 to 100 billion devices connected to the Internet. Two domains of hot resea...