Energy-Efficient Bayesian Inference Using Bitstream Computing
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Computer Architecture Letters"
DOI: 10.1109/lca.2023.3238584
Abstract: Uncertainty quantification is critical to many machine learning applications especially in mobile and edge computing tasks like self-driving cars, robots, and mobile devices. Bayesian Neural Networks can be used to provide these uncertainty quantifications but… read more here.
Keywords: bitstream; efficient bayesian; energy; bayesian inference ... See more keywords
An Energy-Efficient Bayesian Neural Network Implementation Using Stochastic Computing Method.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2023.3265533
Abstract: The robustness of Bayesian neural networks (BNNs) to real-world uncertainties and incompleteness has led to their application in some safety-critical fields. However, evaluating uncertainty during BNN inference requires repeated sampling and feed-forward computing, making them… read more here.
Keywords: bayesian neural; efficient bayesian; energy; stochastic computing ... See more keywords
Efficient Bayesian inference for stochastic agent-based models
Sign Up to like & getrecommendations! Published in 2022 at "PLoS Computational Biology"
DOI: 10.1371/journal.pcbi.1009508
Abstract: The modelling of many real-world problems relies on computationally heavy simulations of randomly interacting individuals or agents. However, the values of the parameters that underlie the interactions between agents are typically poorly known, and hence… read more here.
Keywords: efficient bayesian; machine learning; bayesian inference; real world ... See more keywords
Efficient Bayesian inference for mechanistic modelling with high-throughput data
Sign Up to like & getrecommendations! Published in 2022 at "PLoS Computational Biology"
DOI: 10.1371/journal.pcbi.1010191
Abstract: Bayesian methods are routinely used to combine experimental data with detailed mathematical models to obtain insights into physical phenomena. However, the computational cost of Bayesian computation with detailed models has been a notorious problem. Moreover,… read more here.
Keywords: efficient bayesian; bayesian inference; high throughput; throughput data ... See more keywords