
Bayesian Neural Networks
The Quant / Financial Engineering Podcast
Enhancing Bayesian Neural Networks with Synthetic and Real Data
This chapter explores data-driven strategies for selecting activation functions in Bayesian Neural Networks, utilizing insights from learned weights during training. By combining synthetic and real data, the chapter aims to enhance model accuracy and reliability while minimizing uncertainty.
00:00
Transcript
Play full episode
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.