2 citations · 4 across the 4 of their papers we have counts for
4 papers
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck +3
Linear recurrent neural networks enable powerful long-range sequence modeling with constant memory usage and time-per-token during inference. These architectures hold promise for s…
A Diagonal Structured State Space Model on Loihi 2 for Efficient Streaming Sequence Processing
Svea Marie Meyer, Philipp Weidel, Philipp Plank +4
Deep State-Space Models (SSM) demonstrate state-of-the art performance on long-range sequence modeling tasks. While the recurrent structure of SSMs can be efficiently implemented a…
Solving QUBO on the Loihi 2 Neuromorphic Processor
Alessandro Pierro, Philipp Stratmann, Gabriel Andres Fonseca Guerra +4
In this article, we describe an algorithm for solving Quadratic Unconstrained Binary Optimization problems on the Intel Loihi 2 neuromorphic processor. The solver is based on a har…
Neuromorphic quadratic programming for efficient and scalable model predictive control
Ashish Rao Mangalore, Gabriel Andres Fonseca Guerra, Sumedh R. Risbud +2
Applications in robotics or other size-, weight- and power-constrained autonomous systems at the edge often require real-time and low-energy solutions to large optimization problem…