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Found 2 papers, 1 papers with code
Curiosity & Entropy Driven Unsupervised RL in Multiple Environments
We primarily propose and experiment with five new modifications to the original work: sampling trajectories using an entropy-based probability distribution, dynamic alpha, higher KL Divergence threshold, curiosity-driven exploration, and alpha-percentile sampling on curiosity.
Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields
We present Canonical Field Network (CaFi-Net), a self-supervised method to canonicalize the 3D pose of instances from an object category represented as neural fields, specifically neural radiance fields (NeRFs).
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