104 Open source projects that are alternatives of or similar to scLearn

Improved Deep Metric Learning with Multi-class N-pair Loss Objective

A collection of ORM-style clients to public patent data

(CVPR 2020) This repo contains code for "PADS: Policy-Adapted Sampling for Visual Similarity Learning", which proposes learnable triplet mining with Reinforcement Learning.

All-in-one analysis pipeline

Deep metric learning methods implemented in Chainer

A collection of 50+ trajectory inference methods within a common interface 📥📤

A Bayesian model for compositional single-cell data analysis

This is a repository of my coursera Machine Learning by Standford, Andrew NG course's assignments

Accelerated deep learning R&D

Contains coursera robotics specialization assignment codes

Official PyTorch implementation of "Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning" (AAAI 2021)

PyTorch implementation of “Negative Margin Matters: Understanding Margin in Few-shot Classification”

Code for CVPR 2019 paper "Deep Metric Learning to Rank"

Population assignment analysis using R

Differential expression analysis for single-cell RNA-seq data.

CellRank for directed single-cell fate mapping

A Tensorflow retrieval (space embedding) baseline. Metric learning baseline on CUB and Stanford Online Products.

NLP Specialization (Natural Language Processing) made by deeplearning.ai

Local Fisher Discriminant Analysis in R

Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

Highly efficient PyTorch version of the Semi-hard Triplet loss ⚡️

A PyTorch framework for an image retrieval task including implementation of N-pair Loss (NIPS 2016) and Angular Loss (ICCV 2017).

This repository contains the code implementation used in the paper Temporally Coherent Embeddings for Self-Supervised Video Representation Learning (TCE).

Code for the paper "A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses" (ECCV 2020 - Spotlight)

Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning" (Neural Networks 2022 - in submission)

Deep Learning based cell composition analysis with Scaden.

Polysemous Visual-Semantic Embedding for Cross-Modal Retrieval (CVPR 2019)

Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.

MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition

Single-cell Orientation Tracing

awesome few shot / meta learning papers

Learning Tree structures and Tree metrics

PyTorch code for BMVC 2018 paper: "Self-Paced Learning with Adaptive Visual Embeddings"

scisorseqr is an R-package for processing of single-cell long read data and analyzing differential isoform expression across any two conditions

Wasserstein Generative Adversarial Network for analysing scRNAseq data

Code for Supervised Word Mover's Distance (SWMD)

Awesome Few-shot learning

Generalized Deep Metric Learning.

List of test assignments. ⚡

📆 The infrastructure deployment time machine

PyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"

Single-cell exploratory data analysis for RNA-Seq

Test collection for KIT programming assignments (WS16/17)

Scripts to run and benchmark scRNA-seq cell cluster labeling methods

Source code for the paper "Divide and Conquer the Embedding Space for Metric Learning", CVPR 2019

Code for the empty droplet and cell detection project from the HCA Hackathon.

PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR) in ICLR 2016.

Generalized Product Quantization Network For Semi-supervised Image Retrieval - CVPR 2020

(ICML 2020) This repo contains code for our paper "Revisiting Training Strategies and Generalization Performance in Deep Metric Learning" (https://arxiv.org/abs/2002.08473) to facilitate consistent research in the field of Deep Metric Learning.

Deep Metric and Hash Code Learning Network for Content Based Retrieval of Remote Sensing Images

SegSort: Segmentation by Discriminative Sorting of Segments

Context-Aware Visual Compatibility Prediction (https://arxiv.org/abs/1902.03646)

The corresponding code from our paper "DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations". Do not hesitate to open an issue if you run into any trouble!

Processing of single cell RNAseq data for the recovery of TCRs in python

A R framework for pipeline benchmarking, with application to single-cell RNAseq

Tensorflow implementation for paper: Learning to Compare: Relation Network for Few-Shot Learning.

Code for NeurIPS 2019 Paper

Papers and Codes about Deep Metric Learning/Deep Embedding

Spatial Single Cell Analysis in Python

R package to visualize gene expression data based on weighted kernel density estimation