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Hello,
The following code snippet shows a custom distance function that scales the simple dot distance with the rewards associated with each embedding.
```python
import torch
from pytorch_metr…
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Hello, in your paper you mentioned that you implemented the paper "Weakly supervised scene parsing with point-based distance metric learning" . Could you please post this part of the code? thank you …
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# Feature Request: Integrate Dimension Insensitive Euclidean Metric (DIEM) into Qdrant
## Background
We have come across a paper that proposes a novel distance metric called **Dimension Insensitiv…
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Methods that we haven't implemented yet, but would like to. In no particular order:
- [ ] [Probablistic Global Distance Metric Learning](http://www.cs.cmu.edu/~liuy/frame_survey_v2.pdf)
- Probabil…
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References ;-
https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.DistanceMetric.html ---> (A Guide for various distance metrics, so just refer the mathematical formulas, then imple…
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# Task Name
Audio Spatial Distance Prediction
## Task Objective
Audio Spatial Distance Prediction is a task that aims to predict spatial distance from the source of the sound based on the giv…
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**Description:**
I would like to propose the addition of a new loss function and detector to the pytorch-ood library: an Angular Loss function (e.g., ArcFace) and an Angle-Based Detector. These add…
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I am trying to use this package to build neighbor lists. I am new to Julia. Can you help me in the implementation of periodic elucidation distance or add it as a functionality?
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#### Description
Hi, is there going to be some metric learning algorithm on the semi-supervised direction, utilising both labels/pairwise constraints and unlabelled data to derive the distance metr…
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Hi. I am using `pairwise_distance` Python API to calculate Jaccard distance and wonder how I can apply this on GPU. With `faiss.pairwise_distances(embeddings, embeddings, faiss.METRIC_Jaccard)`, you o…