Review on metal halide perovskite-based optoelectronic synapses
X Hong, X Liu, L Liao, X Zou - Photonics Research, 2023 - opg.optica.org
With the progress of both photonics and electronics, optoelectronic synapses are considered
potential candidates to challenge the von Neumann bottleneck and the field of visual bionics …
potential candidates to challenge the von Neumann bottleneck and the field of visual bionics …
Graphd: Graph-based hyperdimensional memorization for brain-like cognitive learning
Memorization is an essential functionality that enables today's machine learning algorithms
to provide a high quality of learning and reasoning for each prediction. Memorization gives …
to provide a high quality of learning and reasoning for each prediction. Memorization gives …
Biohd: an efficient genome sequence search platform using hyperdimensional memorization
In this paper, we propose BioHD, a novel genomic sequence searching platform based on
Hyper-Dimensional Computing (HDC) for hardware-friendly computation. BioHD transforms …
Hyper-Dimensional Computing (HDC) for hardware-friendly computation. BioHD transforms …
Recent progress and development of hyperdimensional computing (hdc) for edge intelligence
Brain-inspired Hyperdimensional Computing (HDC) is an emerging framework in low-
energy designs for solving classification tasks at the edge. Unlike mainstream neural …
energy designs for solving classification tasks at the edge. Unlike mainstream neural …
Learning from hypervectors: A survey on hypervector encoding
Hyperdimensional computing (HDC) is an emerging computing paradigm that imitates the
brain's structure to offer a powerful and efficient processing and learning model. In HDC, the …
brain's structure to offer a powerful and efficient processing and learning model. In HDC, the …
Memory-inspired spiking hyperdimensional network for robust online learning
Recently, brain-inspired computing models have shown great potential to outperform today's
deep learning solutions in terms of robustness and energy efficiency. Particularly, Spiking …
deep learning solutions in terms of robustness and energy efficiency. Particularly, Spiking …
Hypergraf: Hyperdimensional graph-based reasoning acceleration on fpga
The latest hardware accelerators proposed for graph applications primarily focus on graph
neural networks (GNNs) and graph mining. High-level graph reasoning tasks, such as graph …
neural networks (GNNs) and graph mining. High-level graph reasoning tasks, such as graph …
Eventhd: Robust and efficient hyperdimensional learning with neuromorphic sensor
Brain-inspired computing models have shown great potential to outperform today's deep
learning solutions in terms of robustness and energy efficiency. Particularly, Hyper …
learning solutions in terms of robustness and energy efficiency. Particularly, Hyper …
Hdgim: Hyperdimensional genome sequence matching on unreliable highly scaled fefet
This is the first work to present a reliable application for highly scaled (down to merely 3nm),
multi-bit Ferroelectric FET (FeFET) technology. FeFET is one of the up-and-coming …
multi-bit Ferroelectric FET (FeFET) technology. FeFET is one of the up-and-coming …
Brain-inspired computing for in-process melt pool characterization in additive manufacturing
Melt pool dynamics represent key information on defect creation in the laser powder bed
fusion (LBPF) additive manufacturing process. In-situ sensing of the melt pool is now …
fusion (LBPF) additive manufacturing process. In-situ sensing of the melt pool is now …