A virtual rodent predicts the structure of neural activity across behaviours

Author:

Aldarondo DiegoORCID,Merel Josh,Marshall Jesse D.ORCID,Hasenclever Leonard,Klibaite Ugne,Gellis Amanda,Tassa YuvalORCID,Wayne Greg,Botvinick MatthewORCID,Ölveczky Bence P.ORCID

Publisher

Springer Science and Business Media LLC

Reference73 articles.

1. Merel, J. et al. Deep neuroethology of a virtual rodent. In Proc. 8th International Conference on Learning Representations 11686–11705 (ICLR, 2020).

2. Todorov, E., Erez, T. & Tassa, Y. MuJoCo: a physics engine for model-based control. In Proc. 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems 5026–5033 (IEEE, 2012).

3. Hasenclever, L., Pardo, F., Hadsell, R., Heess, N. & Merel, J. CoMic: complementary task learning & mimicry for reusable skills. In Proc. 37th International Conference on Machine Learning (eds Daumé, H. & Singh, A.) 4105–4115 (PMLR, 2020).

4. Merel, J. et al. Neural probabilistic motor primitives for humanoid control. In Proc. 7th International Conference on Learning Representations (ICLR, 2019).

5. Peng, X. B., Abbeel, P., Levine, S. & van de Panne, M. DeepMimic: example-guided deep reinforcement learning of physics-based character skills. ACM Trans. Graph. 37, 1–14 (2018).

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