ECD reformulates compositional diffusion planning as energy minimization over local bridge potentials, adding a boundary reaction term and a Markov score approximation that runs in linear time.
Dolan, and Jeff Schneider
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
verdicts
UNVERDICTED 3representative citing papers
RCD steers compositional diffusion sampling toward high-density coherent plans by combining reconstruction-error guidance with overlap consistency, outperforming prior methods on locomotion, manipulation, and pixel-based long-horizon tasks.
BYOL-γ uses self-predictive representations to approximate successor representations, improving zero-shot combinatorial generalization in goal-conditioned behavioral cloning.
citing papers explorer
-
Energy-based Compositional Diffusion Planning
ECD reformulates compositional diffusion planning as energy minimization over local bridge potentials, adding a boundary reaction term and a Markov score approximation that runs in linear time.
-
Refining Compositional Diffusion for Reliable Long-Horizon Planning
RCD steers compositional diffusion sampling toward high-density coherent plans by combining reconstruction-error guidance with overlap consistency, outperforming prior methods on locomotion, manipulation, and pixel-based long-horizon tasks.
-
Self-Predictive Representations for Combinatorial Generalization in Behavioral Cloning
BYOL-γ uses self-predictive representations to approximate successor representations, improving zero-shot combinatorial generalization in goal-conditioned behavioral cloning.