Pinned Repositories
PICA
Official Pytorch Implementation for CVPR'20 paper: Deep Semantic Clustering by Partition Confidence Maximisation
align_uniform
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere.
bio_corex
A flexible version of CorEx developed for bio-data challenges that handles missing data, continuous/discrete variables, multi-CPU, overlapping structure, and includes visualizations
bioc2017singlecell
Bioconductor2017 workshop - Analysis of single-cell RNA-seq data: Normalization, dimensionality reduction, clustering, and lineage inference
cca_zoo
Canonical Correlation Analysis Model Zoo: Standard: CCA, GCCA, MCCA, TCCA, KCCA, TKCCA, sparse CCA , ridge CCA and elastic CCA, PMD, PLS. Deep: DCCA, DMCCA, DGCCA, DTCCA. DVCCA, DCCAE, SplitAE. Probabilistic: VBCCCA. With simulated data generation and toy datasets.
ClusterGAN
Latent space clustering in Generative Adversarial Network (GAN)
clusterGAN-1
Pytorch Implementation of ClusterGAN (arXiv:1809.03627)
clustering_on_transcript_compatibility_counts
Clustering cells from single cell RNA seq assays
Contrastive-Clustering
Code for the paper "Contrastive Clustering" (AAAI 2021)
CorEx
CorEx or "Correlation Explanation" discovers a hierarchy of informative latent factors. This reference implementation has been superseded by other versions below.
fffaby's Repositories
fffaby/fffaby.github.io
Homepage about FangfeiLin.
fffaby/FangfeiLin.github.io
fffaby/fffaby
fffaby/CVPR2021-Papers-with-Code
CVPR 2021 论文和开源项目合集
fffaby/papernotclear
fffaby/pvae
code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".
fffaby/align_uniform
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere.
fffaby/pytorch-metric-learning
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
fffaby/Contrastive-Clustering
Code for the paper "Contrastive Clustering" (AAAI 2021)
fffaby/cca_zoo
Canonical Correlation Analysis Model Zoo: Standard: CCA, GCCA, MCCA, TCCA, KCCA, TKCCA, sparse CCA , ridge CCA and elastic CCA, PMD, PLS. Deep: DCCA, DMCCA, DGCCA, DTCCA. DVCCA, DCCAE, SplitAE. Probabilistic: VBCCCA. With simulated data generation and toy datasets.
fffaby/triplet-loss-pytorch
Highly efficient PyTorch version of the Semi-hard Triplet loss ⚡️
fffaby/python-img_gist_feature
Implement extracting Gist feature from a image (Matlab LMGist)
fffaby/fashion-mnist
A MNIST-like fashion product database. Benchmark :point_down:
fffaby/HGCAE
HGCAE Pytorch implementation. CVPR2021 accepted.
fffaby/lemniscate.pytorch
Unsupervised Feature Learning via Non-parametric Instance Discrimination
fffaby/hyperbolic_nn_plusplus
Official PyTorch implementation of Hyperbolic Neural Networks++
fffaby/mvc
fffaby/HypHC
Hyperbolic Hierarchical Clustering.
fffaby/Unsupervised-Classification
SCAN: Learning to Classify Images without Labels (ECCV 2020)
fffaby/hyperbolic_nn
Source code for the paper "Hyperbolic Neural Networks", https://arxiv.org/abs/1805.09112
fffaby/DeepClustering
Methods and Implements of Deep Clustering
fffaby/corex_topic
Hierarchical unsupervised and semi-supervised topic models for sparse count data with CorEx
fffaby/pt-dec
PyTorch implementation of DEC (Deep Embedding Clustering)
fffaby/bio_corex
A flexible version of CorEx developed for bio-data challenges that handles missing data, continuous/discrete variables, multi-CPU, overlapping structure, and includes visualizations
fffaby/desc
Deep Embedding for Single-cell Clustering
fffaby/pytorch-book
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
fffaby/mvgrl
fffaby/PICA
Official Pytorch Implementation for CVPR'20 paper: Deep Semantic Clustering by Partition Confidence Maximisation
fffaby/DeepCCA-1
An implementation of Deep Canonical Correlation Analysis (DCCA or Deep CCA) with pytorch.
fffaby/netNMF-sc
netNMF-sc: A network regularization algorithm for dimensionality reduction and imputation of single-cell expression data