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cs.LG2026
Outperforming 1000 Euclidean Layers With Hyperbolic Goal-Conditioned RL
Timo Klein, Thomas Lang, Andrii Shkabrii +3
Scaling self-supervised contrastive reinforcement learning (CRL) to 1000-layer Euclidean neural networks has enabled state-of-the-art goal-reaching performance, yet wall-clock time…
cs.LG2024
Discrete Modeling via Boundary Conditional Diffusion Processes
Yuxuan Gu, Xiaocheng Feng, Lei Huang +5
We present an novel framework for efficiently and effectively extending the powerful continuous diffusion processes to discrete modeling. Previous approaches have suffered from the…