Reservoir Computing

This page contains all content related to Reservoir Computing research, an innovative approach to machine learning using dynamical systems.

Research Focus

  • Performance-driven Evolution: Developing networks that evolve to optimize computational performance
  • Network Pruning: Identifying and removing unnecessary nodes while maintaining or improving performance
  • Bio-inspired Architectures: Creating reservoir computers inspired by biological neural networks
  • Structural Optimization: Understanding the relationship between network structure and computational function

Browse the content below to explore publications, projects, and collaborations in reservoir computing.

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Evolution beats random chance: Performance-dependent network evolution for enhanced computational capacity featured image

Evolution beats random chance: Performance-dependent network evolution for enhanced computational capacity

Can evolution beat random chances? Our answer: Yes, we have a proof! 😃

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Dr. Manish Yadav

Denoising and reconstruction of nonlinear dynamics using truncated reservoir computing

This paper presents a novel RC method for noise filtering and reconstructing unobserved nonlinear dynamics, offering a novel learning protocol associated with hyperparameter …

Omid Sedehi
Predicting multi-parametric dynamics of an externally forced oscillator using reservoir computing and minimal data featured image

Predicting multi-parametric dynamics of an externally forced oscillator using reservoir computing and minimal data

This study uses a data-driven approach to investigate how bifurcations can be learned from a few system response measurements.

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Dr. Manish Yadav
Session Organization at Dynamics Days Europe, Bremen 2024 featured image

Session Organization at Dynamics Days Europe, Bremen 2024

The contributed session on Dynamics on graphs was chaired by Dr. Manish Yadav in the reputed international conference of Dynamics Days 2024, Bremen.

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Music generation with bucket of water based Physical Reservoir Computer featured image

Music generation with bucket of water based Physical Reservoir Computer

Project Planning The next phase of of the project of information processing with bucket of water based Physcial Reservoir Computers is being planned to generate music with it. …

DFG SPP 2353 Jahrestreffen 2024, Bergisch Gladbach featured image

DFG SPP 2353 Jahrestreffen 2024, Bergisch Gladbach

Talk presented at the DFG SPP 2353 Annual Meeting in Bergisch Gladbach 2024.

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Dr. Manish Yadav
DFG SPP Doktorandtreffen 2024, Mainz featured image

DFG SPP Doktorandtreffen 2024, Mainz

Talk on Reservoir Computing as design assistants under limited data at the DFG SPP 2353 Doktorandtreffen 2024.

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Dr. Manish Yadav

Data Driven Dynamics (D3) Community 2024

Talk on Reservoir Computing for time-Series prediction presented at the Data Driven Dynamics (D3) Community meeting.

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Dr. Manish Yadav

Prof. Merten Stender

Prof. Merten Stender is leading the Cyber-Physical Systems in Mechanical Engineering department at TU Berlin. Our collaboration focuses on developing dynamics-informed machine …

Prof. Eduardo Miranda

Prof. Eduardo Miranda is a renowned composer and Professor in computer music at the University of Plymouth, UK. Our collaboration focuses on developing music generation systems …