👋 Hello
I'm Daniel Bethell
Research Associate in AI at University of York working on uncertainty quantification, safe reinforcement learning, and trustworthy machine learning.
Recent
Robust Adversarial Quantification via Conflict-Aware Evidential Deep Learning
·2126 words·10 mins·
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Uncertainty
Evidential Deep Learning
Papers Explained
Learning to Navigate Under Imperfect Perception: Conformalised Segmentation for Safe Reinforcement Learning
·2503 words·12 mins·
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Uncertainty
Conformal Prediction
Safe Reinforcement Learning
Papers Explained
Do Some Research Areas Get an Easier Accept? The Quiet Biases Hiding in ICLR's Peer Review
·2684 words·13 mins·
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Discussion
Safe Reinforcement Learning in Black-Box Environments via Adaptive Shielding
·1969 words·10 mins·
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Safe Reinforcement Learning
Shielding
Papers Explained
A Comprehensive Guide to Conformal Prediction: Simplifying the Math, and Code
·14601 words·69 mins·
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Uncertainty
Conformal Prediction
Demystifying Kolmogorov-Arnold Networks: A Beginner-Friendly Guide with Code
·2347 words·12 mins·
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Kolmogorov-Arnold Networks