A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning

Marco Fraccaro, Simon Kamronn, Ulrich Paquet, Ole Winther

Nov-21-2025, 11:17:30 GMT–Neural Information Processing Systems

From the earliest stages of childhood, humans learn to represent high-dimensional sensory input to make temporal predictions. From the visual image of a moving tennis ball, we can imagine its trajectory, and prepare ourselves in advance to catch it.

artificial intelligence, kv ae, machine learning, (18 more...)

Neural Information Processing Systems

Nov-21-2025, 11:17:30 GMT

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  - Representation & Reasoning > Uncertainty (0.68)
  - Machine Learning
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    - Statistical Learning (0.68)
    - Learning Graphical Models (0.68)

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A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning
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