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#

feature-learning

Here are 47 public repositories matching this topic...

Pytorch implementation of Center Loss

  • UpdatedFeb 19, 2023
  • Python

[ICCV 2025] PartField: Learning 3D Feature Fields for Part Segmentation and Beyond

  • UpdatedJul 16, 2025
  • Python

[CVPR 2017] Unsupervised deep learning using unlabelled videos on the web

  • UpdatedApr 25, 2019
  • Lua
getml-community

Fast, high-quality forecasts on relational and multivariate time-series data powered by new feature learning algorithms and automated ML.

  • UpdatedOct 27, 2025
  • C++

Experiments on unsupervised point cloud reconstruction.

  • UpdatedJun 11, 2022
  • Python

DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DOF Relocalization

  • UpdatedNov 11, 2020
  • Python

A simple Tensorflow based library for deep and/or denoising AutoEncoder.

  • UpdatedApr 7, 2018
  • Python

Leveraging Inlier Correspondences Proportion for Point Cloud Registration.https://arxiv.org/abs/2201.12094.

  • UpdatedApr 2, 2023
  • Python

OhmNet: Representation learning in multi-layer graphs

  • UpdatedAug 12, 2020
  • Python

Temporal-spatial Feature Learning of DCE-MR Images via 3DCNN

  • UpdatedMay 19, 2019
  • Python

Feature learning over RDF data and OWL ontologies

  • UpdatedAug 17, 2022
  • Python

Deep Co-occurrence Feature Learning for Visual Object Recognition (CVPR 2017)

  • UpdatedMay 15, 2017
  • MATLAB

Code for paper "Learning Semantically Enhanced Feature for Fine-grained Image Classification"

  • UpdatedAug 30, 2020
  • Python

[NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization

  • UpdatedMay 27, 2025
  • Python

Easy-to-read implementation of self-supervised learning using vision transformer and knowledge distillation with no labels 😃

  • UpdatedJun 27, 2023
  • Python

Experiments on point cloud segmentation.

  • UpdatedJun 11, 2022
  • Python

Repository for SEPAL: Scalable Feature Learning on Huge Knowledge Graphs for Downstream Machine Learning

  • UpdatedNov 20, 2025
  • Python

A comprehensive deep dive into how Variational Autoencoders (VAEs) learn to generate realistic synthetic tabular data. This project explores latent space learning, probabilistic modeling, and neural creativity, combining data privacy, interpretability, and generative AI techniques in a structured format.

  • UpdatedNov 10, 2025

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