4 papers
Algorithm and Hardware Co-Design for Efficient Complex-Valued Uncertainty Estimation
Zehuan Zhang, Mark Chen, He Li +1
Complex-Valued Neural Networks (CVNNs) have significant advantages in handling tasks that involve complex numbers. However, existing CVNNs are unable to quantify predictive uncerta…
Advancing AI-assisted Hardware Design with Hierarchical Decentralized Training and Personalized Inference-Time Optimization
Hao Mark Chen, Zehuan Zhang, Wanru Zhao +2
Recent years have witnessed a significant increase in the adoption of AI techniques to enhance electronic design automation. In particular, the emergence of Large Language Models (…
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…
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…