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cs.LG2022
Learning Control by Iterative Inversion
Gal Leibovich, Guy Jacob, Or Avner +2
We propose -- an algorithm for learning an inverse function without input-output pairs, but only with samples from the desired output distribution an…
cs.LG2022
Meta Reinforcement Learning with Finite Training Tasks -- a Density Estimation Approach
Zohar Rimon, Aviv Tamar, Gilad Adler
In meta reinforcement learning (meta RL), an agent learns from a set of training tasks how to quickly solve a new task, drawn from the same task distribution. The optimal meta RL p…
cs.CV2022★ 3 cited
Unsupervised Image Representation Learning with Deep Latent Particles
Tal Daniel, Aviv Tamar
We propose a new representation of visual data that disentangles object position from appearance. Our method, termed Deep Latent Particles (DLP), decomposes the visual input into l…