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On the Permutation Invariance of Graph Generative Models
This blog post discusses the permutation invariance principle of graph generative models, which has often been taken for granted in graph-related tasks. While permutation symmetry is an elegant property of graph data, there is still more to learn about its empirical implications.
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Conditional Generative Models for Motion Prediction
In this blog post, we discuss good engineering practices and the lessons learned—sometimes the hard way—from building conditional generative models (in particular, flow matching) for motion prediction problems.
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Evaluating Motion Consistency by Fréchet Video Motion Distance (FVMD)
In this blog post, we introduce a promising new metric for video generative models, Fréchet Video Motion Distance (FVMD), which focuses on the motion consistency of generated videos.
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A Review of Video Evaluation Metrics
Video generative models have been rapidly improving recently, but how do we evaluate them efficiently and effectively? In this blog post, we review the existing evaluation metrics and highlight their pros and cons.