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 …
Spiking hyperdimensional network: Neuromorphic models integrated with memory-inspired framework
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 …
Scalehd: Robust brain-inspired hyperdimensional computing via adapative scaling
Brain-inspired hyperdimensional computing (HDC) has demonstrated promising capability
in various cognition tasks such as robotics, bio-medical signal analysis, and natural …
in various cognition tasks such as robotics, bio-medical signal analysis, and natural …
Adapthd: Adaptive efficient training for brain-inspired hyperdimensional computing
Brain-inspired Hyperdimensional (HD) computing is a promising solution for energy-efficient
classification. HD emulates cognition tasks by exploiting long-size vectors instead of working …
classification. HD emulates cognition tasks by exploiting long-size vectors instead of working …
Stochd: Stochastic hyperdimensional system for efficient and robust learning from raw data
Hyperdimensional Computing (HDC) is a neurally-inspired computation model working
based on the observation that the human brain operates on high-dimensional …
based on the observation that the human brain operates on high-dimensional …
Assessing robustness of hyperdimensional computing against errors in associative memory
Brain-inspired hyperdimensional computing (HDC) is an emerging computational paradigm
that has achieved success in various domains. HDC mimics brain cognition and lever-ages …
that has achieved success in various domains. HDC mimics brain cognition and lever-ages …
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 …
Exploring embedding methods in binary hyperdimensional computing: A case study for motor-imagery based brain-computer interfaces
Key properties of brain-inspired hyperdimensional (HD) computing make it a prime
candidate for energy-efficient and fast learning in biosignal processing. The main challenge …
candidate for energy-efficient and fast learning in biosignal processing. The main challenge …
Dynamic hyperdimensional computing for improving accuracy-energy efficiency trade-offs
Brain-inspired Hyperdimensional (HD) computing is an emerging technique that computes
with either binary or integer HD vectors. However, both vector representations confront an …
with either binary or integer HD vectors. However, both vector representations confront an …
Hyper-dimensional computing challenges and opportunities for AI applications
Brain-inspired architectures are gaining increased attention, especially for edge devices to
perform cognitive tasks utilizing its limited energy budget and computing resources …
perform cognitive tasks utilizing its limited energy budget and computing resources …