Memristive technologies for data storage, computation, encryption, and radio-frequency communication
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 …
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
Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …
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 …
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
This two-part comprehensive survey is devoted to a computing framework most commonly
known under the names Hyperdimensional Computing and Vector Symbolic Architectures …
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 …
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
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 …
commonly known under the names Hyperdimensional Computing and Vector Symbolic …
A neuro-vector-symbolic architecture for solving Raven's progressive matrices
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 …
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
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 …
Neuro-Fuzzy Inference System (ANFIS), M5P, and Random Forest (RF) soft-computing …
Vector symbolic architectures as a computing framework for emerging hardware
This article reviews recent progress in the development of the computing framework vector
symbolic architectures (VSA)(also known as hyperdimensional computing). This framework …
symbolic architectures (VSA)(also known as hyperdimensional computing). This framework …
Experimentally validated memristive memory augmented neural network with efficient hashing and similarity search
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 …
learning from few, often single, samples. Memory-augmented neural networks have been …