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aranciokov avatar

aranciokov/NTM-For-RULEstimation

0
View on GitHub↗
4 stars·0 forks·Python·MIT·16 views

NTM For RULEstimation

This repository contains the code accompanying the paper "Neural Turing Machines for the Remaining Useful Life estimation problem", accepted for publication in Computers In Industry.

Features

  • Memory Systems - Neural Turing Machines applied to remaining useful life estimation.

Star history

Star history chart for aranciokov/ntm-for-rulestimationStar history chart for aranciokov/ntm-for-rulestimation

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with NTM For RULEstimation

These projects share indexed features with NTM For RULEstimation. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • facebookresearch/xlmfacebookresearch avatar

    facebookresearch/XLM

    2,930View on GitHub↗

    PyTorch original implementation of Cross-lingual Language Model Pretraining.

    Python
    View on GitHub↗2,930
  • fate-ubw/raglabfate-ubw avatar

    fate-ubw/RAGLAB

    311View on GitHub↗

    EMNLP 2024: Demo Oral RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation

    Python
    View on GitHub↗311
  • ga-s3/social-simulationG

    GA-S3/Social-Simulation

    0View on GitHub↗
    View on GitHub↗0
  • facebookresearch/atlasfacebookresearch avatar

    facebookresearch/atlas

    562View on GitHub↗

    REPO NO LONGER MAINTAINED, RESEARCH CODE PROVIDED AS IT IS

    Python
    View on GitHub↗562
Compare all 13 related projects→

Frequently asked questions

What does aranciokov/ntm-for-rulestimation do?

This repository contains the code accompanying the paper "Neural Turing Machines for the Remaining Useful Life estimation problem", accepted for publication in Computers In Industry.

What are the main features of aranciokov/ntm-for-rulestimation?

The main features of aranciokov/ntm-for-rulestimation are: Memory Systems.

Which projects share features with aranciokov/ntm-for-rulestimation?

Projects with overlapping indexed features include: facebookresearch/xlm — PyTorch original implementation of Cross-lingual Language Model Pretraining. fate-ubw/raglab — [EMNLP 2024: Demo Oral] RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation. ga-s3/social-simulation. lucidrains/titans-pytorch — Unofficial implementation of Titans, SOTA memory for transformers, in Pytorch. ml-jku/hopfield-layers — Hopfield Networks is All You Need. facebookresearch/atlas — REPO NO LONGER MAINTAINED, RESEARCH CODE PROVIDED AS IT IS.