Improve accuracy of a bayesian neural network

I am seeking a skilled professional who can help me improve the accuracy of my Bayesian neural network. The current accuracy of the network is more than 70%, and I am looking to make further enhancements. The model is based off of the "Incorporating Interpretable Output Constraints in Bayesian Neural Networks" paper, and I am planning to use the neural network on proprietary dataset once better accuracy is reached on the publicly available MIMIC III dataset. Please Note: any incremental improvement in accuracy will be paid the full amount of the freelance work, but a mathematical reasoning for what changes were applied needs to be there. Dataset: - I am currently using a publicly available dataset for both training and testing - the MIMIC III dataset. Desired Accuracy Improvement: - I am aiming for an accuracy improvement of 0-3%. Skills and Experience: - Strong knowledge and experience in Bayesian neural networks. - Proficiency in working with publicly available datasets. - Expertise in improving accuracy in machine learning models. - Familiarity with statistical modeling and probability theory. - Attention to detail and ability to analyze data effectively. If you have the necessary skills and experience in Bayesian neural networks and can help me achieve my desired accuracy improvement, I would love to hear from you. Please provide examples of your previous work in this field. The content should not be cheated, and is NOT needed for any assignment/academic cheating. This is to be used in my AI startup in Bangalore, India. If you do the work fine enough, a FT offer might be offered.