From the 1 of 7 linked papers with an AI index.
1 citations · 1 across the 4 of their papers we have counts for
7 papers
The SpiNNaker2 chip: a many-core platform for flexible and scalable brain-inspired computing
Stefan Scholze, Johannes Partzsch, Sebastian Höppner +27
In deep learning, efficiency gets more and more important to compensate for the ongoing growth in model sizes and applications. Neuromorphic hardware has long been advocated as an…
Event-based Neural Decoding for Neuroprosthetic Motor Control
Khaleelulla Khan Nazeer, Sirine Arfa, Matthias Jobst +2
The paper proposes an event‑based gated recurrent unit for neural decoding that generates sparse, graded spikes, enabling low‑latency, low‑power motor control in neuroprosthetic de…
LAYUP: Asynchronous decentralized gradient descent with LAYer-wise UPdates
Cabrel Teguemne Fokam, Marcel Nieveler, Lukas König +3
The increasing size of deep learning models has made distributed training across multiple devices essential. Synchronous, centralized methods incur large communication and synchron…
Heterogeneous computing platform for real-time robotics
Jakub Fil, Yulia Sandamirskaya, Hector Gonzalez +18
After Industry 4.0 has embraced tight integration between machinery (OT), software (IT), and the Internet, creating a web of sensors, data, and algorithms in service of efficient a…
Activity Sparsity Complements Weight Sparsity for Efficient RNN Inference
Rishav Mukherji, Mark Schöne, Khaleelulla Khan Nazeer +2
Artificial neural networks open up unprecedented machine learning capabilities at the cost of ever growing computational requirements. Sparsifying the parameters, often achieved th…
STREAM: A Universal State-Space Model for Sparse Geometric Data
Mark Schöne, Yash Bhisikar, Karan Bania +4
Handling sparse and unstructured geometric data, such as point clouds or event-based vision, is a pressing challenge in the field of machine vision. Recently, sequence models such…