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Found 5 papers, 3 papers with code
Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models
In this paper, we learn dynamics models for parametrized families of dynamical systems with varying properties.
Learning to Identify Physical Parameters from Video Using Differentiable Physics
Video prediction models often learn a latent representation of video which is encoded from input frames and decoded back into images.
Sample-efficient Cross-Entropy Method for Real-time Planning
However, their sampling inefficiency prevents them from being used for real-time planning and control.
Planning from Images with Deep Latent Gaussian Process Dynamics
We propose to learn a deep latent Gaussian process dynamics (DLGPD) model that learns low-dimensional system dynamics from environment interactions with visual observations.
Variational Network Quantization
In this paper, the preparation of a neural network for pruning and few-bit quantization is formulated as a variational inference problem.
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