1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
Enhancing Dropout-based Bayesian Neural Networks with Multi-Exit on FPGA
Hao Mark Chen, Liam Castelli, Martin Ferianc +4
Reliable uncertainty estimation plays a crucial role in various safety-critical applications such as medical diagnosis and autonomous driving. In recent years, Bayesian neural netw…
cs.LG2023
When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA
Hongxiang Fan, Hao Chen, Liam Castelli +4
Bayesian Neural Networks (BayesNNs) have demonstrated their capability of providing calibrated prediction for safety-critical applications such as medical imaging and autonomous dr…