4 papers · 1 filter
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…
COMponent-Aware Pruning for Accelerated Control Tasks in Latent Space Models
Ganesh Sundaram, Jonas Ulmen, Amjad Haider +1
The rapid growth of resource-constrained mobile platforms, including mobile robots, wearable systems, and Internet-of-Things devices, has increased the demand for computationally e…
Application-Specific Component-Aware Structured Pruning of Deep Neural Networks in Control via Soft Coefficient Optimization
Ganesh Sundaram, Jonas Ulmen, Amjad Haider +1
Deep neural networks (DNNs) offer significant flexibility and robust performance. This makes them ideal for building not only system models but also advanced neural network control…
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…