pathak22/unsupervised-video

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

Language: Lua - Size: 336 KB - Last synced at: 7 days ago - Pushed at: about 6 years ago - Stars: 260 - Forks: 51

KaiyangZhou/pytorch-center-loss

Pytorch implementation of Center Loss

Language: Python - Size: 5.54 MB - Last synced at: 7 days ago - Pushed at: about 2 years ago - Stars: 988 - Forks: 219

getml/getml-community

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

Language: Jupyter Notebook - Size: 20.8 MB - Last synced at: about 16 hours ago - Pushed at: 4 months ago - Stars: 115 - Forks: 14

antao97/UnsupervisedPointCloudReconstruction 📦

Experiments on unsupervised point cloud reconstruction.

Language: Python - Size: 13 MB - Last synced at: about 2 months ago - Pushed at: almost 3 years ago - Stars: 166 - Forks: 27

isadrtdinov/understanding-large-lrs

Source code for NeurIPS-2024 paper "Where Do Large Learning Rates Lead Us"

Language: Jupyter Notebook - Size: 1.38 MB - Last synced at: about 5 hours ago - Pushed at: 5 months ago - Stars: 6 - Forks: 0

fatin-farhan/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.

Language: Jupyter Notebook - Size: 1.88 MB - Last synced at: about 2 months ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 0

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

Language: Jupyter Notebook - Size: 111 MB - Last synced at: 10 days ago - Pushed at: almost 3 years ago - Stars: 21 - Forks: 7

GabrielFernandezFernandez/SPIVAE

Stochastic processes insights from VAE. Code for the paper: Learning minimal representations of stochastic processes with variational autoencoders.

Language: Jupyter Notebook - Size: 18.9 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 7 - Forks: 0

JuanDuGit/DH3D

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

Language: Python - Size: 123 MB - Last synced at: 8 days ago - Pushed at: over 4 years ago - Stars: 160 - Forks: 17

DocsaidLab/DocClassifier

A zero-shot document classifier.

Language: Python - Size: 46 MB - Last synced at: 27 days ago - Pushed at: 4 months ago - Stars: 4 - Forks: 1

eigenvivek/Grad-CAMO

[CVPRW 2024] Learning interpretable single-cell morphological profiles from 3D Cell Painting z-stacks

Size: 34.2 KB - Last synced at: about 1 month ago - Pushed at: 10 months ago - Stars: 5 - Forks: 0

LFhase/FeAT

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

Language: Python - Size: 434 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 23 - Forks: 1

sedflix/tripletgan.pytorch

Implementation of the paper Training Triplet Networks with GAN

Language: Jupyter Notebook - Size: 435 KB - Last synced at: 3 months ago - Pushed at: almost 5 years ago - Stars: 2 - Forks: 0

rajarsheem/libsdae-autoencoder-tensorflow

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

Language: Python - Size: 3.1 MB - Last synced at: 24 days ago - Pushed at: about 7 years ago - Stars: 149 - Forks: 39

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

Feature learning over RDF data and OWL ontologies

Language: Python - Size: 1.28 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 44 - Forks: 7

sjenni/LearningToSpotArtifacts

Self-Supervised Feature Learning by Learning to Spot Artifacts. In CVPR, 2018.

Language: Python - Size: 4.98 MB - Last synced at: 10 months ago - Pushed at: about 2 years ago - Stars: 18 - Forks: 1

mims-harvard/ohmnet

OhmNet: Representation learning in multi-layer graphs

Language: Python - Size: 492 KB - Last synced at: 12 months ago - Pushed at: almost 5 years ago - Stars: 78 - Forks: 33

dreizehnutters/pcapAE

convGRU based autoencoder for unsupervised & spatial-temporal anomaly detection in computer network (PCAP) traffic.

Language: Jupyter Notebook - Size: 27.5 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 11 - Forks: 1

zoli333/Center-Loss

This is an implementation of the Center Loss article (2016).

Language: Python - Size: 24.8 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 14 - Forks: 7

xyj77/MCF-3D-CNN

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

Language: Python - Size: 2.26 MB - Last synced at: over 1 year ago - Pushed at: almost 6 years ago - Stars: 46 - Forks: 20

rikturr/mml-feature-learning

Miami Machine Learning Meetup - Feature Learning with Matrix Factorization and Neural Networks

Language: Jupyter Notebook - Size: 4.68 MB - Last synced at: 11 months ago - Pushed at: about 7 years ago - Stars: 10 - Forks: 0

ml-uol/prosper

A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions

Language: Python - Size: 623 KB - Last synced at: almost 2 years ago - Pushed at: over 5 years ago - Stars: 20 - Forks: 9

AntonioScl/SGD_learning_regimes

Code for reproducing the paper "Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning"

Language: Python - Size: 80.1 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

manhph2211/Self-Supervised-Distillation

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

Language: Python - Size: 69.3 KB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 14 - Forks: 1

zhulf0804/NgeNet

Neighborhood-aware Geometric Encoding Network for Point Cloud Registration. https://arxiv.org/abs/2201.12094.

Language: Python - Size: 7.06 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 52 - Forks: 6

cswluo/SEF

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

Language: Python - Size: 1.87 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 25 - Forks: 7

yafangshih/Deep-COOC

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

Language: Matlab - Size: 21.3 MB - Last synced at: about 2 years ago - Pushed at: about 8 years ago - Stars: 35 - Forks: 14

antao97/PointCloudSegmentation

Experiments on point cloud segmentation.

Language: Python - Size: 1.82 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 13 - Forks: 8

hmohebbi/CNN_featureLearning_SVM_classifier

Image Classification via Transfer Learning: Using Pre-trained Densely Connected Convolutional Network (DenseNet) weights

Language: Jupyter Notebook - Size: 1.3 MB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 5 - Forks: 4

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.

Language: C - Size: 31.5 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

sjenni/LCI

Steering Self-Supervised Feature Learning Beyond Local Pixel Statistics. In CVPR, 2020.

Language: Python - Size: 10.2 MB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 14 - Forks: 7

CarsonScott/Competitive-Feature-Learning

Online feature-extraction and classification algorithm that learns representations of input patterns.

Language: C++ - Size: 20.5 KB - Last synced at: about 2 years ago - Pushed at: about 8 years ago - Stars: 31 - Forks: 3

lelea2/kdao

Collections of my personal prototypes for works, hackathon and personal project

Language: JavaScript - Size: 24.4 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

alex-kom/Cluster-HyperEnsembles

Ensembles and hyperparameter optimization for clustering pipelines.

Language: Python - Size: 39.1 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 0

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.

Language: Jupyter Notebook - Size: 76.1 MB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 1 - Forks: 1

INSPIRE-Lab-US/LSR-dictionary-learning

Associated codebase for the paper "Learning Mixtures of Separable Dictionaries for Tensor Data: Analysis and Algorithms"

Language: HTML - Size: 8.46 MB - Last synced at: 3 months ago - Pushed at: almost 5 years ago - Stars: 3 - Forks: 0

chrinide/ohmnet Fork of mims-harvard/ohmnet

Unsupervised feature learning in multi-layer networks

Language: Python - Size: 360 KB - Last synced at: about 2 years ago - Pushed at: about 8 years ago - Stars: 0 - Forks: 0