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stat.ML2024
Quantifying Local Model Validity using Active Learning
Sven Lämmle, Can Bogoclu, Robert Voßhall +2
Real-world applications of machine learning models are often subject to legal or policy-based regulations. Some of these regulations require ensuring the validity of the model, i.e…
cs.LG2024★ 1 cited
Deep Gaussian Covariance Network with Trajectory Sampling for Data-Efficient Policy Search
Can Bogoclu, Robert Vosshall, Kevin Cremanns +1
Probabilistic world models increase data efficiency of model-based reinforcement learning (MBRL) by guiding the policy with their epistemic uncertainty to improve exploration and a…