activity
20222024
most citedWHYPE: A Scale-Out Architecture with Wireless Over-the-Air Majority for Scalable In-memory Hyperdimensional Computing

7 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024

12 mJ per Class On-Device Online Few-Shot Class-Incremental Learning

Yoga Esa Wibowo, Cristian Cioflan, Thorir Mar Ingolfsson +4

Few-Shot Class-Incremental Learning (FSCIL) enables machine learning systems to expand their inference capabilities to new classes using only a few labeled examples, without forget…

cs.CV2024

Zero-shot Classification using Hyperdimensional Computing

Samuele Ruffino, Geethan Karunaratne, Michael Hersche +3

Classification based on Zero-shot Learning (ZSL) is the ability of a model to classify inputs into novel classes on which the model has not previously seen any training examples. P…

cs.LG20241 cited

Probabilistic Abduction for Visual Abstract Reasoning via Learning Rules in Vector-symbolic Architectures

Michael Hersche, Francesco di Stefano, Thomas Hofmann +2

Abstract reasoning is a cornerstone of human intelligence, and replicating it with artificial intelligence (AI) presents an ongoing challenge. This study focuses on efficiently sol…

cs.DC20237 cited

WHYPE: A Scale-Out Architecture with Wireless Over-the-Air Majority for Scalable In-memory Hyperdimensional Computing

Robert Guirado, Abbas Rahimi, Geethan Karunaratne +3

Hyperdimensional computing (HDC) is an emerging computing paradigm that represents, manipulates, and communicates data using long random vectors known as hypervectors. Among differ…

cs.LG20222 cited

In-memory Realization of In-situ Few-shot Continual Learning with a Dynamically Evolving Explicit Memory

Geethan Karunaratne, Michael Hersche, Jovin Langenegger +15

Continually learning new classes from a few training examples without forgetting previous old classes demands a flexible architecture with an inevitably growing portion of storage,…