6 papers
Mixed-signal implementation of feedback-control optimizer for single-layer Spiking Neural Networks
Jonathan Haag, Christian Metzner, Dmitrii Zendrikov +4
On-chip learning is key to scalable and adaptive neuromorphic systems, yet existing training methods are either difficult to implement in hardware or overly restrictive. However, r…
The Cooperative Network Architecture: Learning Structured Networks as Representation of Sensory Patterns
Pascal J. Sager, Jan M. Deriu, Benjamin F. Grewe +2
We introduce the Cooperative Network Architecture (CNA), a model that represents sensory signals using structured, recurrently connected networks of neurons, termed "nets." Nets ar…
Mechanistic Interpretability of RNNs emulating Hidden Markov Models
Elia Torre, Michele Viscione, Lucas Pompe +2
Recurrent neural networks (RNNs) provide a powerful approach in neuroscience to infer latent dynamics in neural populations and to generate hypotheses about the neural computations…
Robust-Sub-Gaussian Model Predictive Control for Safe Ultrasound-Image-Guided Robotic Spinal Surgery
Yunke Ao, Manish Prajapat, Yarden As +6
Safety-critical control using high-dimensional sensory feedback from optical data (e.g., images, point clouds) poses significant challenges in domains like autonomous driving and r…
mimic-one: a Scalable Model Recipe for General Purpose Robot Dexterity
Elvis Nava, Victoriano Montesinos, Erik Bauer +8
We present a diffusion-based model recipe for real-world control of a highly dexterous humanoid robotic hand, designed for sample-efficient learning and smooth fine-motor action in…
Two types of pyramidal cells and their role in temporal processing
Anh Duong Vo, Elisabeth Abs, Pau Vilimelis Aceituno +2
Recent work has provided new insights into the temporal specialization of Intratelencephalic (IT) and Pyramidal tract neurons (PT). However, functional and anatomical differences o…