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Found 2 papers, 1 papers with code
Automatic Truss Design with Reinforcement Learning
Directly applying end-to-end reinforcement learning (RL) methods to truss layout design is infeasible either, since only a tiny portion of the entire layout space is valid under the physical constraints, leading to particularly sparse rewards for RL training.
StyleFlow: Disentangle Latent Representations via Normalizing Flow for Unsupervised Text Style Transfer
Since cycle construction helps to improve the style transfer ability of the model by rebuilding transferred sentences back to original-style sentences, it brings about a content loss in unsupervised text style transfer tasks.
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