Robust high-dimensional memory-augmented neural networks
Sign Up to like & getrecommendations! Published in 2021 at "Nature Communications"
DOI: 10.1038/s41467-021-22364-0
Abstract: Traditional neural networks require enormous amounts of data to build their complex mappings during a slow training procedure that hinders their abilities for relearning and adapting to new data. Memory-augmented neural networks enhance neural networks… read more here.
Keywords: high dimensional; neural networks; augmented neural; explicit memory ... See more keywords
Differentiable Physics Simulation of Dynamics-Augmented Neural Objects
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2023.3257707
Abstract: We present a differentiable pipeline for simulating the motion of objects that represent their geometry as a continuous density field parameterized as a deep network. This includes Neural Radiance Fields (NeRFs), and other related models.… read more here.
Keywords: neural objects; density field; physics; dynamics augmented ... See more keywords
An In-Memory Computing SRAM Macro for Memory-Augmented Neural Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2021.3132063
Abstract: In-Memory Computing (IMC) has been widely studied to mitigate data transfer bottlenecks in von Neumann architectures. Recently proposed IMC circuit topologies dramatically reduce data transfer requirements by performing various operations such as Multiply-Accumulate (MAC) inside… read more here.
Keywords: neural network; augmented neural; memory augmented; sram macro ... See more keywords
A 40-nm Training-Inference STT-MRAM Near-Memory Computing Macro for Memory-Augmented Neural Network Acceleration
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Very Large Scale Integration (VLSI) Systems"
DOI: 10.1109/tvlsi.2025.3597404
Abstract: Recently, memory-augmented neural networks (MANNs) have gained significant attention as a critical solution for few-shot learning (FSL). These networks leverage external memory to store prior knowledge, thereby enhancing classification efficiency. Spin-transfer torque magnetic random access… read more here.
Keywords: memory augmented; memory; stt mram; near memory ... See more keywords