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cs.LG2026
Component-Aware Pruning Framework for Neural Network Controllers via Gradient-Based Importance Estimation
Ganesh Sundaram, Jonas Ulmen, Daniel Görges
The transition from monolithic to multi-component neural architectures in advanced neural network controllers poses substantial challenges due to the high computational complexity…
cs.LG2025
Learning State-Space Models of Dynamic Systems from Arbitrary Data using Joint Embedding Predictive Architectures
Jonas Ulmen, Ganesh Sundaram, Daniel Görges
With the advent of Joint Embedding Predictive Architectures (JEPAs), which appear to be more capable than reconstruction-based methods, this paper introduces a novel technique for…
cs.LG2025
Enhanced Pruning Strategy for Multi-Component Neural Architectures Using Component-Aware Graph Analysis
Ganesh Sundaram, Jonas Ulmen, Daniel Görges
Deep neural networks (DNNs) deliver outstanding performance, but their complexity often prohibits deployment in resource-constrained settings. Comprehensive structured pruning fram…