48 citations · 101 across the 4 of their papers we have counts for
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cs.NE2020★ 42 cited
Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
Rui Wang, Joel Lehman, Aditya Rawal +4
Creating open-ended algorithms, which generate their own never-ending stream of novel and appropriately challenging learning opportunities, could help to automate and accelerate pr…
cs.NE2018
From Nodes to Networks: Evolving Recurrent Neural Networks
Aditya Rawal, Risto Miikkulainen
Gated recurrent networks such as those composed of Long Short-Term Memory (LSTM) nodes have recently been used to improve state of the art in many sequential processing tasks such…
cs.NE2017★ 7 cited
Evolving Deep Neural Networks
Risto Miikkulainen, Jason Liang, Elliot Meyerson +8
The success of deep learning depends on finding an architecture to fit the task. As deep learning has scaled up to more challenging tasks, the architectures have become difficult t…