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Found 3 papers, 1 papers with code
All You Need Is Supervised Learning: From Imitation Learning to Meta-RL With Upside Down RL
Upside down reinforcement learning (UDRL) flips the conventional use of the return in the objective function in RL upside down, by taking returns as input and predicting actions.
Highway and Residual Networks learn Unrolled Iterative Estimation
We demonstrate that this viewpoint directly leads to the construction of Highway and Residual networks.
Compete to Compute
Local competition among neighboring neurons is common in biological neural networks (NNs).
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