Accelerating SE(3)-Transformers Training Using an NVIDIA Open-Source Model Implementation

SE(3)-Transformers are versatile graph neural networks unveiled at NeurIPS 2020. NVIDIA just released an open-source optimized implementation that uses 9x less memory and is up to 21x faster than the baseline official implementation. SE(3)-Transformers are useful in dealing with problems with geometric symmetries, like small molecules processing, protein refinement, or point cloud applications. They can … Continued...

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