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GraphMDN: Leveraging graph structure and deep learning to solve inverse problems
The recent introduction of Graph Neural Networks (GNNs) and their growing popularity in the past few years has enabled the application of deep learning algorithms to non-Euclidean, graph-structured data.
Graph Classification
Multi-Hypotheses 3D Human Pose Estimation
+2
Compete to Compute
Local competition among neighboring neurons is common in biological neural networks (NNs).
Autonomous Reinforcement of Behavioral Sequences in Neural Dynamics
We introduce a dynamic neural algorithm called Dynamic Neural (DN) SARSA(\lambda) for learning a behavioral sequence from delayed reward.
