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benemer commented Jun 18, 2021


In kaolin/kaolin/metrics/ it says that the sided_distance() method computes

For every point in p1 find the indices and euclidean distances of the closest point in p2.

However, it seems like the underlying _C.metrics.sided_distance_forward_cuda returns the squared euclidean distance. Can you please clarify this?

Thank you

documentation good first issue question

A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

  • Updated May 18, 2022
  • Python

The Model Zoo of Cognitive Diagnosis Models, including classic Item Response Ranking (IRT), Multidimensional Item Response Ranking (MIRT), Deterministic Input, Noisy "And" model(DINA), and advanced Fuzzy Cognitive Diagnosis Framework (FuzzyCDF), Neural Cognitive Diagnosis Model (NCDM) and Item Response Ranking framework (IRR).

  • Updated Jan 30, 2022
  • Python

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