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Matching Networks for One Shot Learning

, , , , and . Proceedings of the Neural Information Processing Systems Conference, page 3630--3638. (2016)

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Matching Networks for One Shot Learning, , , , and . Proceedings of the Neural Information Processing Systems Conference, page 3630--3638. (2016)Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model, , , , , , , , , and 2 other author(s). (2019)cite arxiv:1911.08265.A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play, , , , , , , , , and 3 other author(s). Science, 362 (6419): 1140--1144 (2018)Learning to Learn for Global Optimization of Black Box Functions., , , , , and . CoRR, (2016)Meta-Learning Deep Energy-Based Memory Models., , , and . ICLR, OpenReview.net, (2020)Deep Learning with Dynamic Spiking Neurons and Fixed Feedback Weights., , and . Neural Comput., 29 (3): 578-602 (2017)Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning., , , , , , , , , and 13 other author(s). CoRR, (2021)Android in the Wild: A Large-Scale Dataset for Android Device Control., , , , and . CoRR, (2023)One-shot Learning with Memory-Augmented Neural Networks., , , , and . CoRR, (2016)Learning Latent Dynamics for Planning from Pixels., , , , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 2555-2565. PMLR, (2019)