On Accelerating Diffusion-based Molecular Conformation Generation in SE(3)-invariant Space
This addresses a bottleneck for researchers and practitioners in computational chemistry by enabling faster molecular conformation generation, though it is incremental as it builds on existing diffusion-based methods.
The paper tackles the slow generation of molecular conformations using diffusion models in SE(3)-invariant space by developing a novel acceleration scheme, achieving a 50x to 100x speedup while maintaining high-quality results.
Diffusion-based generative models in SE(3)-invariant space have demonstrated promising performance in molecular conformation generation, but typically require solving stochastic differential equations (SDEs) with thousands of update steps. Till now, it remains unclear how to effectively accelerate this procedure explicitly in SE(3)-invariant space, which greatly hinders its wide application in the real world. In this paper, we systematically study the diffusion mechanism in SE(3)-invariant space via the lens of approximate errors induced by existing methods. Thereby, we develop more precise approximate in SE(3) in the context of projected differential equations. Theoretical analysis is further provided as well as empirical proof relating hyper-parameters with such errors. Altogether, we propose a novel acceleration scheme for generating molecular conformations in SE(3)-invariant space. Experimentally, our scheme can generate high-quality conformations with 50x--100x speedup compared to existing methods.