A neural machine code and programming framework for the reservoir computer
JZ Kim, DS Bassett - Nature Machine Intelligence, 2023 - nature.com
From logical reasoning to mental simulation, biological and artificial neural systems possess
an incredible capacity for computation. Such neural computers offer a fundamentally novel …
an incredible capacity for computation. Such neural computers offer a fundamentally novel …
Biological neurons act as generalization filters in reservoir computing
T Sumi, H Yamamoto, Y Katori, K Ito… - Proceedings of the …, 2023 - National Acad Sciences
Reservoir computing is a machine learning paradigm that transforms the transient dynamics
of high-dimensional nonlinear systems for processing time-series data. Although the …
of high-dimensional nonlinear systems for processing time-series data. Although the …
Connectivity, dynamics, and memory in reservoir computing with binary and analog neurons
Reservoir computing (RC) systems are powerful models for online computations on input
sequences. They consist of a memoryless readout neuron that is trained on top of a …
sequences. They consist of a memoryless readout neuron that is trained on top of a …
Hands-on reservoir computing: a tutorial for practical implementation
This manuscript serves a specific purpose: to give readers from fields such as material
science, chemistry, or electronics an overview of implementing a reservoir computing (RC) …
science, chemistry, or electronics an overview of implementing a reservoir computing (RC) …
A survey on reservoir computing and its interdisciplinary applications beyond traditional machine learning
Reservoir computing (RC), first applied to temporal signal processing, is a recurrent neural
network in which neurons are randomly connected. Once initialized, the connection …
network in which neurons are randomly connected. Once initialized, the connection …
Minimal approach to neuro-inspired information processing
To learn and mimic how the brain processes information has been a major research
challenge for decades. Despite the efforts, little is known on how we encode, maintain and …
challenge for decades. Despite the efforts, little is known on how we encode, maintain and …
Memory in linear recurrent neural networks in continuous time
M Hermans, B Schrauwen - Neural Networks, 2010 - Elsevier
Reservoir Computing is a novel technique which employs recurrent neural networks while
circumventing difficult training algorithms. A very recent trend in Reservoir Computing is the …
circumventing difficult training algorithms. A very recent trend in Reservoir Computing is the …
A novel approach to minimal reservoir computing
H Ma, D Prosperino, C Räth - Scientific Reports, 2023 - nature.com
Reservoir computers are powerful machine learning algorithms for predicting nonlinear
systems. Unlike traditional feedforward neural networks, they work on small training data …
systems. Unlike traditional feedforward neural networks, they work on small training data …
Evolutionary aspects of reservoir computing
LF Seoane - … Transactions of the Royal Society B, 2019 - royalsocietypublishing.org
Reservoir computing (RC) is a powerful computational paradigm that allows high versatility
with cheap learning. While other artificial intelligence approaches need exhaustive …
with cheap learning. While other artificial intelligence approaches need exhaustive …
On computational power and the order-chaos phase transition in reservoir computing
B Schrauwen, L Büsing… - Advances in neural …, 2008 - proceedings.neurips.cc
Randomly connected recurrent neural circuits have proven to be very powerful models for
online computations when a trained memoryless re adout function is appended. Such …
online computations when a trained memoryless re adout function is appended. Such …