3 citations · 6 across the 12 of their papers we have counts for
4 papers · 1 filter
Accelerating MRI Uncertainty Estimation with Mask-based Bayesian Neural Network
Zehuan Zhang, Matej Genci, Hongxiang Fan +2
Accurate and reliable Magnetic Resonance Imaging (MRI) analysis is particularly important for adaptive radiotherapy, a recent medical advance capable of improving cancer diagnosis…
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…
Hardware-Aware Neural Dropout Search for Reliable Uncertainty Prediction on FPGA
Zehuan Zhang, Hongxiang Fan, Hao Mark Chen +2
The increasing deployment of artificial intelligence (AI) for critical decision-making amplifies the necessity for trustworthy AI, where uncertainty estimation plays a pivotal role…
Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference
Hao Mark Chen, Wayne Luk, Ka Fai Cedric Yiu +4
The auto-regressive decoding of Large Language Models (LLMs) results in significant overheads in their hardware performance. While recent research has investigated various speculat…