Simplified Diffusion Schrödinger Bridge

• URL: http://arxiv.org/abs/2403.14623v3
• Date: Mon, 27 May 2024 04:44:22 GMT
• Title: Simplified Diffusion Schrödinger Bridge
• Authors: Zhicong Tang, Tiankai Hang, Shuyang Gu, Dong Chen, Baining Guo,
• Abstract summary: This paper introduces a novel theoretical simplification of the Diffusion Schr"odinger Bridge (DSB) It addresses the limitations of DSB in complex data generation and enables faster convergence and enhanced performance.
• Score: 24.492662903341966
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper introduces a novel theoretical simplification of the Diffusion Schr\"odinger Bridge (DSB) that facilitates its unification with Score-based Generative Models (SGMs), addressing the limitations of DSB in complex data generation and enabling faster convergence and enhanced performance. By employing SGMs as an initial solution for DSB, our approach capitalizes on the strengths of both frameworks, ensuring a more efficient training process and improving the performance of SGM. We also propose a reparameterization technique that, despite theoretical approximations, practically improves the network's fitting capabilities. Our extensive experimental evaluations confirm the effectiveness of the simplified DSB, demonstrating its significant improvements. We believe the contributions of this work pave the way for advanced generative modeling. The code is available at https://github.com/checkcrab/SDSB.

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