Machine Learning

This page contains all content related to Machine Learning research, including applications in reservoir computing, network analysis, and bio-inspired systems.

Key Research Areas

  • Reservoir Computing: Developing efficient machine learning approaches using dynamical systems
  • Network-based ML: Machine learning on complex networks and graph structures
  • Bio-inspired Learning: Learning algorithms inspired by biological information processing

Browse the content below to explore publications, projects, and collaborations in machine learning.

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
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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
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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
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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
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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 …

DFG SPP 2353: Dynamics-Informed Reservoir Computing (DIRC) featured image

DFG SPP 2353: Dynamics-Informed Reservoir Computing (DIRC)

This project is part of the DFG Priority Program SPP 2353: Daring More Intelligence – Design Assistants in Mechanics and Dynamics, funded by the German Research Foundation (DFG). …