Memristive technologies for data storage, computation, encryption, and radio-frequency communication

M Lanza, A Sebastian, WD Lu, M Le Gallo, MF Chang… - Science, 2022 - science.org
Memristive devices, which combine a resistor with memory functions such that voltage
pulses can change their resistance (and hence their memory state) in a nonvolatile manner …

Recent advances and future prospects for memristive materials, devices, and systems

MK Song, JH Kang, X Zhang, W Ji, A Ascoli… - ACS …, 2023 - ACS Publications
Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …

Constrained few-shot class-incremental learning

M Hersche, G Karunaratne… - Proceedings of the …, 2022 - openaccess.thecvf.com
Continually learning new classes from fresh data without forgetting previous knowledge of
old classes is a very challenging research problem. Moreover, it is imperative that such …

A survey on hyperdimensional computing aka vector symbolic architectures, part i: Models and data transformations

D Kleyko, DA Rachkovskij, E Osipov… - ACM Computing …, 2022 - dl.acm.org
This two-part comprehensive survey is devoted to a computing framework most commonly
known under the names Hyperdimensional Computing and Vector Symbolic Architectures …

Echo state graph neural networks with analogue random resistive memory arrays

S Wang, Y Li, D Wang, W Zhang, X Chen… - Nature Machine …, 2023 - nature.com
Recent years have witnessed a surge of interest in learning representations of graph-
structured data, with applications from social networks to drug discovery. However, graph …

A survey on hyperdimensional computing aka vector symbolic architectures, part ii: Applications, cognitive models, and challenges

D Kleyko, D Rachkovskij, E Osipov, A Rahimi - ACM Computing Surveys, 2023 - dl.acm.org
This is Part II of the two-part comprehensive survey devoted to a computing framework most
commonly known under the names Hyperdimensional Computing and Vector Symbolic …

A neuro-vector-symbolic architecture for solving Raven's progressive matrices

M Hersche, M Zeqiri, L Benini, A Sebastian… - Nature Machine …, 2023 - nature.com
Neither deep neural networks nor symbolic artificial intelligence (AI) alone has approached
the kind of intelligence expressed in humans. This is mainly because neural networks are …

Wave height predictions in complex sea flows through soft-computing models: Case study of Persian Gulf

T Sadeghifar, GFC Lama, P Sihag, A Bayram, O Kisi - Ocean Engineering, 2022 - Elsevier
The present study case examined the capability of Artificial Neural Network (ANN), Adaptive
Neuro-Fuzzy Inference System (ANFIS), M5P, and Random Forest (RF) soft-computing …

Vector symbolic architectures as a computing framework for emerging hardware

D Kleyko, M Davies, EP Frady, P Kanerva… - Proceedings of the …, 2022 - ieeexplore.ieee.org
This article reviews recent progress in the development of the computing framework vector
symbolic architectures (VSA)(also known as hyperdimensional computing). This framework …

Experimentally validated memristive memory augmented neural network with efficient hashing and similarity search

R Mao, B Wen, A Kazemi, Y Zhao, AF Laguna… - Nature …, 2022 - nature.com
Lifelong on-device learning is a key challenge for machine intelligence, and this requires
learning from few, often single, samples. Memory-augmented neural networks have been …