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See and Copy: Generation of complex compositional movements from modular and geometric RNN representations
A hallmark of biological intelligence and control is combinatorial generalization: animals are able to learn various things, then piece them together in new combinations to produce appropriate outputs for new tasks.
Representation learning for improved interpretability and classification accuracy of clinical factors from EEG
Despite extensive standardization, diagnostic interviews for mental health disorders encompass substantial subjective judgment.
Unsupervised Model Selection for Variational Disentangled Representation Learning
Disentangled representations have recently been shown to improve fairness, data efficiency and generalisation in simple supervised and reinforcement learning tasks.
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