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Found 4 papers, 1 papers with code
Active Learning on Neural Networks through Interactive Generation of Digit Patterns and Visual Representation
In this paper, to improve users' learning and understanding of NNs, an interactive learning system is designed to create digit patterns and recognize them in real time.
Uncertainty-Aware Reward-based Deep Reinforcement Learning for Intent Analysis of Social Media Information
Distinguishing the types of fake news spreaders based on their intent is critical because it will effectively guide how to intervene to mitigate the spread of fake news with different approaches.
PPO-UE: Proximal Policy Optimization via Uncertainty-Aware Exploration
Proximal Policy Optimization (PPO) is a highly popular policy-based deep reinforcement learning (DRL) approach.
A Survey on Uncertainty Reasoning and Quantification for Decision Making: Belief Theory Meets Deep Learning
We found that only a few studies have leveraged the mature uncertainty research in belief/evidence theories in ML/DL to tackle complex problems under different types of uncertainty.
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