feature-learning

There are 4 repositories under feature-learning topic.

KaiyangZhou / pytorch-center-loss
Pytorch implementation of Center Loss
pytorch deep-learning center-loss python loss-functions feature-learning computer-vision
Language:Python 939
pathak22 / unsupervised-video
[CVPR 2017] Unsupervised deep learning using unlabelled videos on the web
unsupervised-learning deep-learning video-processing video-segmentation machine-learning computer-vision motion-segmentation feature-learning
Language:Lua 259
antao97 / UnsupervisedPointCloudReconstruction
Experiments on unsupervised point cloud reconstruction.
pytorch point-cloud unsupervised-learning auto-encoder feature-learning
Language:Python 158
JuanDuGit / DH3D
DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DOF Relocalization
autonomous-driving deep-learning feature-learning point-cloud relocalization
Language:Python 155
rajarsheem / libsdae-autoencoder-tensorflow
A simple Tensorflow based library for deep and/or denoising AutoEncoder.
autoencoder deep-learning feature-learning
Language:Python 148
zhulf0804 / GCNet
Leveraging Inlier Correspondences Proportion for Point Cloud Registration. https://arxiv.org/abs/2201.12094.
feature-learning pointcloud registration
Language:Python 87
mims-harvard / ohmnet
OhmNet: Representation learning in multi-layer graphs
multi-layer neural-embeddings bioinformatics genomics feature-learning deep-learning
Language:Python 78
getml-community
getml / getml-community
Fast, high-quality forecasts on relational and multivariate time-series data powered by new feature learning algorithms and automated ML.
ai data-science feature-engineering feature-learning machine-learning ml mlops predictive-modeling python-library relational-learning
Language:C 77
xyj77 / MCF-3D-CNN
Temporal-spatial Feature Learning of DCE-MR Images via 3DCNN
3dcnn dce-mri feature-learning fusion keras medical-images temporal-spatial
Language:Python 46
bio-ontology-research-group / walking-rdf-and-owl
Feature learning over RDF data and OWL ontologies
classification feature-learning machine-learning owl rdf-graph semantic-web
Language:Python 44
yafangshih / Deep-COOC
Deep Co-occurrence Feature Learning for Visual Object Recognition (CVPR 2017)
cvpr-2017 image-recognition recognition co-occurence feature-learning object-recognition computer-vision
Language:MATLAB 36
cswluo / SEF
Code for paper "Learning Semantically Enhanced Feature for Fine-grained Image Classification"
fine-grained-visual-categorization feature-learning image-classification
Language:Python 32
CarsonScott / Competitive-Feature-Learning
Online feature-extraction and classification algorithm that learns representations of input patterns.
machine-learning classification feature-learning feature-extraction feature-detection pattern-recognition compression competitive-learning artificial-intelligence pattern-classification pattern dimensionality-reduction threshold online-learning
Language:C++ 31
bruAristimunha / Re-Deep-Convolution-Neural-Network-and-Autoencoders-Based-Unsupervised-Feature-Learning-of-EEG
autoencoder deep-learning eeg-signals epileptic-seizures feature-learning
Language:Jupyter Notebook 20
ml-uol / prosper
A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions
machine-learning sparse-coding feature-learning probabilistic-graphical-models variational-inference
Language:Python 20
antao97 / PointCloudSegmentation
Experiments on point cloud segmentation.
unsupervised-learning segmentation point-cloud feature-learning
Language:Python 19
manhph2211 / Self-Supervised-Distillation
Easy-to-read implementation of self-supervised learning using vision transformer and knowledge distillation with no labels - DINO :smiley:
self-supervised dino feature-learning knowledge-distillation attention-visualization contrastive-learning ema feature-representation teacher-student-training vision-transformer
Language:Python 18
sjenni / LearningToSpotArtifacts
Self-Supervised Feature Learning by Learning to Spot Artifacts. In CVPR, 2018.
self-supervised-learning unsupervised-learning tensorflow stl-10 alexnet deep-learning machine-learning compter-vision feature-learning classification
Language:Python 18
LFhase / FeAT
[NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization
domain-generalization feature-learning invariant-learning out-of-distribution-generalization spurious-correlations
Language:Python 17
sjenni / LCI
Steering Self-Supervised Feature Learning Beyond Local Pixel Statistics. In CVPR, 2020.
feature-learning inpainting self-supervised-learning stl10 tensorflow transfer-learning unsupervised-learning
Language:Python 15
zoli333 / Center-Loss
This is an implementation of the Center Loss article (2016).
deep-learning center-loss feature-learning pytorch
Language:Python 14
dreizehnutters / pcapAE
convGRU based autoencoder for unsupervised & spatial-temporal anomaly detection in computer network (PCAP) traffic.
anomaly-detection autoencoder feature-learning intrusion-detection machine-learning network pcap representation-learning
Language:Jupyter Notebook 11
rikturr / mml-feature-learning
Miami Machine Learning Meetup - Feature Learning with Matrix Factorization and Neural Networks
matrix-factorization neural-network deep-learning pca autoencoder feature-learning feature-extraction feature-engineering
Language:Jupyter Notebook 10
GabrielFernandezFernandez / SPIVAE
Stochastic processes insights from VAE. Code for the paper: Learning minimal representations of stochastic processes with variational autoencoders.
anomalous-diffusion autoregressive-models brownian-motion feature-learning fractional-brownian-motion interpretability knowledge-discovery representation-learning stochastic-models time-series unsupervised-machine-learning variational-autoencoder scaled-brownian-motion single-trajectory-characterization
Language:Jupyter Notebook 6
hmohebbi / CNN_featureLearning_SVM_classifier
Image Classification via Transfer Learning: Using Pre-trained Densely Connected Convolutional Network (DenseNet) weights
densenet cnn feature-learning pre-trained imagenet svm t-sne pca dimensionality-reduction
Language:Jupyter Notebook 6
zacrash / world-models-feature-learning
Experiment with World Models by Ha et al. using Variational Recurrent Neural Networks for more task relevant feature learning
machine-learning deep-learning robotics feature-learning reinforcement-learning pytorch
Language:Jupyter Notebook 6
DocsaidLab / DocClassifier
A zero-shot document classifier.
clip document-classification feature-learning lightning partial-fc python pytorch zero-shot-learning
Language:Python 3
LSR-dictionary-learning
INSPIRE-Lab-US / LSR-dictionary-learning
Associated codebase for the paper "Learning Mixtures of Separable Dictionaries for Tensor Data: Analysis and Algorithms"
data-driven-learning dictionary-learning feature-learning machine-learning reproducible-research tensor-data
Language:HTML 3
alex-kom / Cluster-HyperEnsembles
Ensembles and hyperparameter optimization for clustering pipelines.
clustering ensemble hyperparameter-optimization consensus-algorithm feature-learning
Language:Python 2
EEE17A / DNN-for-NILM
In this project, we've tried applying various DNNs to the problem of non-intrusive load monitoring (NILM) and compared their results for various appliances using the REDD dataset. We took a sliding window approach in hopes that we'll be able to achieve real time disaggregation with further tuning and testing. We compare the disaggregated energy consumption results based on MSE, MAE, Relative Error and F1 Score.
energy-disaggregation neural-networks feature-learning nilm energy-consumption deep-learning cnn-model load-disaggregation load-forecasting lstm-model
Language:Jupyter Notebook 2
AntonioScl / SGD_learning_regimes
Code for reproducing the paper "Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning"
deep-learning feature-learning lazy-learning stochastic-gradient-descent
Language:Python 1
cocoakang / colmap_multichannel
A modified COLMAP to take as input multi-channel images. It can be used to evaluate the proposed multi-channel feature/descriptor.
3d-reconstruction feature-learning stereo-vision
Language:C 1
eigenvivek / zlearn
Learning interpretable single-cell morphological profiles from 3D Cell Painting z-stacks
cell-painting feature-learning single-cell
1
lelea2 / kdao
Collections of my personal prototypes for works, hackathon and personal project
feature-learning hackathon-ideas prototype
Language:JavaScript 1
sedflix / tripletgan.pytorch
Implementation of the paper Training Triplet Networks with GAN
gan triplet-loss feature-learning unsupervised-feature-learning
Language:Jupyter Notebook 1
swastishreya / Feature-Learning
We aim to illustrate the difference between feature extraction and feature learning. We see that when using classical machine learning models, there is a requirement to come up with features (input to the model) “explicitly”, that would give the best and suitable output for the task in hand. However, when using deep learning models, these features are derived “implicitly” by the model as the training progresses.
computer-vision convolutional-neural-networks feature-learning
Language:Jupyter Notebook 1

feature-learning

KaiyangZhou / pytorch-center-loss

pathak22 / unsupervised-video

antao97 / UnsupervisedPointCloudReconstruction

JuanDuGit / DH3D

rajarsheem / libsdae-autoencoder-tensorflow

zhulf0804 / GCNet

mims-harvard / ohmnet

getml / getml-community

xyj77 / MCF-3D-CNN

bio-ontology-research-group / walking-rdf-and-owl

yafangshih / Deep-COOC

cswluo / SEF

CarsonScott / Competitive-Feature-Learning

bruAristimunha / Re-Deep-Convolution-Neural-Network-and-Autoencoders-Based-Unsupervised-Feature-Learning-of-EEG

ml-uol / prosper

antao97 / PointCloudSegmentation

manhph2211 / Self-Supervised-Distillation

sjenni / LearningToSpotArtifacts

LFhase / FeAT

sjenni / LCI

zoli333 / Center-Loss

dreizehnutters / pcapAE

rikturr / mml-feature-learning

GabrielFernandezFernandez / SPIVAE

hmohebbi / CNN_featureLearning_SVM_classifier

zacrash / world-models-feature-learning

DocsaidLab / DocClassifier

INSPIRE-Lab-US / LSR-dictionary-learning

alex-kom / Cluster-HyperEnsembles

EEE17A / DNN-for-NILM

AntonioScl / SGD_learning_regimes

cocoakang / colmap_multichannel

eigenvivek / zlearn

lelea2 / kdao

sedflix / tripletgan.pytorch

swastishreya / Feature-Learning