3 citations · 3 across the 12 of their papers we have counts for
5 papers · 1 filter
Smartpixels: Towards on-sensor inference of charged particle track parameters and uncertainties
Jennet Dickinson, Rachel Kovach-Fuentes, Lindsey Gray +20
The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-g…
Attention for Causal Relationship Discovery from Biological Neural Dynamics
Ziyu Lu, Anika Tabassum, Shruti Kulkarni +4
This paper explores the potential of the transformer models for learning Granger causality in networks with complex nonlinear dynamics at every node, as in neurobiological and biop…
Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning
Jieun Yoo, Jennet Dickinson, Morris Swartz +19
Highly granular pixel detectors allow for increasingly precise measurements of charged particle tracks. Next-generation detectors require that pixel sizes will be further reduced,…
On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments
Shruti R. Kulkarni, Aaron Young, Prasanna Date +12
This work describes the investigation of neuromorphic computing-based spiking neural network (SNN) models used to filter data from sensor electronics in high energy physics experim…
SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing
Prasanna Date, Chathika Gunaratne, Shruti Kulkarni +3
In many neuromorphic workflows, simulators play a vital role for important tasks such as training spiking neural networks (SNNs), running neuroscience simulations, and designing, i…