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Found 2 papers, 1 papers with code
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
We introduce Deep Adaptive Design (DAD), a method for amortizing the cost of adaptive Bayesian experimental design that allows experiments to be run in real-time.
Distributional Reinforcement Learning for Risk-Sensitive Policies
We address the problem of learning a risk-sensitive policy based on the CVaR risk measure using distributional reinforcement learning.
Distributional Reinforcement Learning
reinforcement-learning
+1
