41 citations · 101 across the 8 of their papers we have counts for
10 papers
A Grid Cell-Inspired Structured Vector Algebra for Cognitive Maps
Sven Krausse, Emre Neftci, Friedrich T. Sommer +1
The entorhinal-hippocampal formation is the mammalian brain's navigation system, encoding both physical and abstract spaces via grid cells. This system is well-studied in neuroscie…
Accurate Mapping of RNNs on Neuromorphic Hardware with Adaptive Spiking Neurons
Gauthier Boeshertz, Giacomo Indiveri, Manu Nair +1
Thanks to their parallel and sparse activity features, recurrent neural networks (RNNs) are well-suited for hardware implementation in low-power neuromorphic hardware. However, map…
Distributed Representations Enable Robust Multi-Timescale Symbolic Computation in Neuromorphic Hardware
Madison Cotteret, Hugh Greatorex, Alpha Renner +6
Programming recurrent spiking neural networks (RSNNs) to robustly perform multi-timescale computation remains a difficult challenge. To address this, we describe a single-shot weig…
NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems
Jason Yik, Korneel Van den Berghe, Douwe den Blanken +97
Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research fiel…
Visual Odometry with Neuromorphic Resonator Networks
Alpha Renner, Lazar Supic, Andreea Danielescu +4
Visual Odometry (VO) is a method to estimate self-motion of a mobile robot using visual sensors. Unlike odometry based on integrating differential measurements that can accumulate…
Neuromorphic Visual Scene Understanding with Resonator Networks
Alpha Renner, Lazar Supic, Andreea Danielescu +5
Analyzing a visual scene by inferring the configuration of a generative model is widely considered the most flexible and generalizable approach to scene understanding. Yet, one maj…
Event-driven Vision and Control for UAVs on a Neuromorphic Chip
Antonio Vitale, Alpha Renner, Celine Nauer +2
Event-based vision sensors achieve up to three orders of magnitude better speed vs. power consumption trade off in high-speed control of UAVs compared to conventional image sensors…
The Backpropagation Algorithm Implemented on Spiking Neuromorphic Hardware
Alpha Renner, Forrest Sheldon, Anatoly Zlotnik +2
The capabilities of natural neural systems have inspired new generations of machine learning algorithms as well as neuromorphic very large-scale integrated (VLSI) circuits capable…
Visual Pattern Recognition with on On-chip Learning: towards a Fully Neuromorphic Approach
Sandro Baumgartner, Alpha Renner, Raphaela Kreiser +3
We present a spiking neural network (SNN) for visual pattern recognition with on-chip learning on neuromorphichardware. We show how this network can learn simple visual patterns co…
Event-based attention and tracking on neuromorphic hardware
Alpha Renner, Matthew Evanusa, Yulia Sandamirskaya
We present a fully event-driven vision and processing system for selective attention and tracking, realized on a neuromorphic processor Loihi interfaced to an event-based Dynamic V…