# Efficient Optimisation of Physical Reservoir Computers using only a Delayed Input

arXiv: https://arxiv.org/abs/2401.14371 · HTML: https://mlsanity.com/paper/2401.14371/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 44 references that are in the map.
- First posted on arXiv 25 Jan 2024.

## Builds on (most cited first, 16 of 16)

- [Next Generation Reservoir Computing](https://mlsanity.com/paper/2106.07688/) (2021)
- [Using a reservoir computer to learn chaotic attractors, with applications to chaos synchronisation and cryptography](https://mlsanity.com/paper/1802.02844/) (2018)
- [Human action recognition with a large-scale brain-inspired photonic computer](https://mlsanity.com/paper/2004.02545/) (2020)
- [Bayesian optimization of hyper-parameters in reservoir computing](https://mlsanity.com/paper/1611.05193/) (2016)
- [Bayesian optimisation of large-scale photonic reservoir computers](https://mlsanity.com/paper/2004.02535/) (2020)
- [Online Training of an Opto-Electronic Reservoir Computer Applied to Real-Time Channel Equalisation](https://mlsanity.com/paper/1610.06268/) (2016)
- [Large-scale spatiotemporal photonic reservoir computer for image classification](https://mlsanity.com/paper/2004.02542/) (2020)
- [High Speed Human Action Recognition using a Photonic Reservoir Computer](https://mlsanity.com/paper/2305.15283/) (2023)
- [Deep Photonic Reservoir Computer for Speech Recognition](https://mlsanity.com/paper/2312.06558/) (2023)
- [Classification of time-domain waveforms using a speckle-based optical reservoir computer](https://mlsanity.com/paper/1909.12489/) (2019)
- [RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization](https://mlsanity.com/paper/2207.05870/) (2022)
- [Re-visiting Reservoir Computing architectures optimized by Evolutionary Algorithms](https://mlsanity.com/paper/2211.06254/) (2022)
- [Reducing hyperparameter dependence by external timescale tailoring](https://mlsanity.com/paper/2307.08603/) (2023)
- [Embodiment of Learning in Electro-Optical Signal Processors](https://mlsanity.com/paper/1610.06269/) (2016)
- [56 GBaud PAM-4 100 km Transmission System with Photonic Processing Schemes](https://mlsanity.com/paper/2105.07990/) (2021)
- [Wavelength-multiplexed Delayed Inputs for Memory Enhancement of Microring-based Reservoir Computing](https://mlsanity.com/paper/2312.04204/) (2023)

## Built on by (most cited first, 3 of 3)

- [Reservoir Computing with a Single Oscillating Gas Bubble: Emphasizing the Chaotic Regime](https://mlsanity.com/paper/2504.07221/) (2025)
- [Bayesian Optimization of Multi-Bit Pulse Encoding in In2O3/Al2O3 Thin-film Transistors for Temporal Data Processing](https://mlsanity.com/paper/2510.07421/) (2025)
- [Adaptive Sensing of Continuous Physical Systems for Machine Learning](https://mlsanity.com/paper/2603.03650/) (2026)

## Abstract (arXiv)

We present an experimental validation of a recently proposed optimization technique for reservoir computing, using an optoelectronic setup. Reservoir computing is a robust framework for signal processing applications, and the development of efficient optimization approaches remains a key challenge. The technique we address leverages solely a delayed version of the input signal to identify the optimal operational region of the reservoir, simplifying the traditionally time-consuming task of hyperparameter tuning. We verify the effectiveness of this approach on different benchmark tasks and reservoir operating conditions.