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We extend pymarl2 to pymarl3, equipping the MARL algorithms with permutation invariance and permutation equivariance properties. The enhanced algorithm achieves 100% win rates on SMAC-V1 and superior performance on SMAC-V2.
Lorentz group equivariant autoencoders based on Lorentz Group Network
Implementation of Pooling by Sliced-Wasserstein Embedding (NeurIPS 2021)
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs
Graph neural network autoencoders for jets in HEP