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Found 2 papers, 2 papers with code
Universally Expressive Communication in Multi-Agent Reinforcement Learning
Allowing agents to share information through communication is crucial for solving complex tasks in multi-agent reinforcement learning.
Beta-VAE Reproducibility: Challenges and Extensions
$\beta$-VAE is a follow-up technique to variational autoencoders that proposes special weighting of the KL divergence term in the VAE loss to obtain disentangled representations.
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