2 papers
cs.LG2025
Exploring Code Language Models for Automated HLS-based Hardware Generation: Benchmark, Infrastructure and Analysis
Jiahao Gai, Hao Mark Chen, Zhican Wang +4
Recent advances in code generation have illuminated the potential of employing large language models (LLMs) for general-purpose programming languages such as Python and C++, openin…
cs.LG2024
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…