Search Results for author:
Found 2 papers, 1 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.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
