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Found 4 papers, 4 papers with code
Learning a Diffusion Model Policy from Rewards via Q-Score Matching
However, previous works fail to exploit the score-based structure of diffusion models, and instead utilize a simple behavior cloning term to train the actor, limiting their ability in the actor-critic setting.
Representation Learning via Manifold Flattening and Reconstruction
This work proposes an algorithm for explicitly constructing a pair of neural networks that linearize and reconstruct an embedded submanifold, from finite samples of this manifold.
Pursuit of a Discriminative Representation for Multiple Subspaces via Sequential Games
We consider the problem of learning discriminative representations for data in a high-dimensional space with distribution supported on or around multiple low-dimensional linear subspaces.
Closed-Loop Data Transcription to an LDR via Minimaxing Rate Reduction
In particular, we propose to learn a closed-loop transcription between a multi-class multi-dimensional data distribution and a linear discriminative representation (LDR) in the feature space that consists of multiple independent multi-dimensional linear subspaces.
