👋 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
Visualising How Neural Networks Learn
·1380 words·7 mins·
loading
·
loading
Neural Networks
Robust Adversarial Quantification via Conflict-Aware Evidential Deep Learning
·2126 words·10 mins·
loading
·
loading
Uncertainty
Evidential Deep Learning
Papers Explained
Learning to Navigate Under Imperfect Perception: Conformalised Segmentation for Safe Reinforcement Learning
·2503 words·12 mins·
loading
·
loading
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·
loading
·
loading
Discussion
Safe Reinforcement Learning in Black-Box Environments via Adaptive Shielding
·1969 words·10 mins·
loading
·
loading
Safe Reinforcement Learning
Shielding
Papers Explained
A Comprehensive Guide to Conformal Prediction: Simplifying the Math, and Code
·14601 words·69 mins·
loading
·
loading
Uncertainty
Conformal Prediction