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Found 3 papers, 2 papers with code
Efficient Certified Training and Robustness Verification of Neural ODEs
Neural Ordinary Differential Equations (NODEs) are a novel neural architecture, built around initial value problems with learned dynamics which are solved during inference.
Remember and Forget Experience Replay for Multi-Agent Reinforcement Learning
We present the extension of the Remember and Forget for Experience Replay (ReF-ER) algorithm to Multi-Agent Reinforcement Learning (MARL).
A Neuro-vector-symbolic Architecture for Solving Raven's Progressive Matrices
Compared to state-of-the-art deep neural network and neuro-symbolic approaches, end-to-end training of NVSA achieves a new record of 87. 7% average accuracy in RAVEN, and 88. 1% in I-RAVEN datasets.
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