activity
20242026
collaborators

5 papers

nlin.AO2026

Emergent E-I Structure in Performance-Evolved Reservoir Networks of Neuronal Population Dynamics

Manish Yadav

Understanding how network structure gives rise to neuronal dynamics and whether compact computational models can recover that structure from data alone is a central challenge in co…

cs.LG2025

Denoising and Reconstruction of Nonlinear Dynamics using Truncated Reservoir Computing

Omid Sedehi, Manish Yadav, Merten Stender +1

Measurements acquired from distributed physical systems are often sparse and noisy. Therefore, signal processing and system identification tools are required to mitigate noise effe…

physics.comp-ph2025

Node pruning reveals compact and optimal substructures within large networks

Manish Yadav, Merten Stender

The structural complexity of reservoir networks poses a significant challenge, often leading to excessive computational costs and suboptimal performance. In this study, we introduc…

cs.CY2024

Data Publishing in Mechanics and Dynamics: Challenges, Guidelines, and Examples from Engineering Design

Henrik Ebel, Jan van Delden, Timo Lüddecke +15

Data-based methods have gained increasing importance in engineering, especially but not only driven by successes with deep artificial neural networks. Success stories are prevalent…

eess.SY2024

The impact of AI on engineering design procedures for dynamical systems

Kristin M. de Payrebrune, Kathrin Flaßkamp, Tom Ströhla +19

Artificial intelligence (AI) is driving transformative changes across numerous fields, revolutionizing conventional processes and creating new opportunities for innovation. The dev…