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Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks
Contrary to prior work, we propose a novel 2D--3D aggregation mechanism based on a differentiable solver for the \emph{Fused Gromov-Wasserstein Barycenter} problem and the use of an efficient online conformer generation method based on distance geometry.
Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models
Learning priors on trajectory distributions can help accelerate robot motion planning optimization.
Hierarchical Policy Blending As Optimal Transport
We present hierarchical policy blending as optimal transport (HiPBOT).
Learning Implicit Priors for Motion Optimization
In this paper, we focus on the problem of integrating Energy-based Models (EBM) as guiding priors for motion optimization.
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