---
title: "DataSP: A Differentiable All-to-All Shortest Path Machine Learning Algorithm to Facilitate Learning Latent Costs from Trajectories"
url: https://daily.dev/posts/datasp-a-differentiable-all-to-all-shortest-path-machine-learning-algorithm-to-facilitate-learning--cjpsdhxzl
source_url: https://www.marktechpost.com/2024/05/15/datasp-a-differentiable-all-to-all-shortest-path-machine-learning-algorithm-to-facilitate-learning-latent-costs-from-trajectories/
type: article
source: "Machine Learning News"
published: 2024-05-15T11:05:29.545Z
updated: 2024-05-15T11:05:28.560Z
tags: ["machine-learning", "neural-networks"]
reading_time: 3
upvotes: 1
comments: 0
language: en
---

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# DataSP: A Differentiable All-to-All Shortest Path Machine Learning Algorithm to Facilitate Learning Latent Costs from Trajectories

**[Machine Learning News](https://daily.dev/sources/mlnews)** · 3 min read · 1 upvotes · 0 comments

## Summary

A novel method called DataSP is proposed to learn latent costs from observed trajectories by encoding them into frequencies of observed shortcuts. DataSP is a differentiable adaptation of the Floyd-Warshall algorithm that enables informative backpropagation through shortest-path computation. It facilitates predicting likely trajectories and inferring probable destinations or future nodes.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.marktechpost.com/2024/05/15/datasp-a-differentiable-all-to-all-shortest-path-machine-learning-algorithm-to-facilitate-learning-latent-costs-from-trajectories/>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#neural-networks](https://daily.dev/tags/neural-networks)

[View this post on daily.dev](https://daily.dev/posts/datasp-a-differentiable-all-to-all-shortest-path-machine-learning-algorithm-to-facilitate-learning--cjpsdhxzl)