CellRank's reproducibility repository.

Overview

CellRank's reproducibility repository

We believe that reproducibility is key and have made it as simple as possible to reproduce our results. Please either open an issue or contact as at [email protected] should you experience difficulties reproducing any result.

Manuscript, code and data

CellRank is published in Nature Methods and the software package can be found at our main website, cellrank.org. Raw published data is available from the Gene Expression Omnibus (GEO) under accession codes:

Processed data, including spliced and unspliced count abundances, is available on figshare. To ease reproducibility, our data examples can also be accessed through CellRank's dataset interface.

Navigating this repository

We've organized this repository along the categories below. For each item, you can click the link under nbviewer to open the notebook in the browser using nbviewer. There is no 1-1 mapping from figures to notebooks - some notebooks produce panels for several figures, and some figures contain panels from several notebooks. The tables we provide here make the connection between figures and notebooks explicit. At the top of each notebook, we indicate the package versions we use.

Results

Main Figures
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Extended Data Figures
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Supplementary Figures
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Supplementary Fig. 17 NA (microscopy results) NA (microscopy results)
Supplementary Tables
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Owner
Theis Lab
Institute of Computational Biology
Theis Lab
PyTorch implementations of the paper: "DR.VIC: Decomposition and Reasoning for Video Individual Counting, CVPR, 2022"

DRNet for Video Indvidual Counting (CVPR 2022) Introduction This is the official PyTorch implementation of paper: DR.VIC: Decomposition and Reasoning

tao han 35 Nov 22, 2022
ruptures: change point detection in Python

Welcome to ruptures ruptures is a Python library for off-line change point detection. This package provides methods for the analysis and segmentation

Charles T. 1.1k Jan 03, 2023
An implementation of a discriminant function over a normal distribution to help classify datasets.

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Dev Sony 6 Nov 09, 2021
Learning where to learn - Gradient sparsity in meta and continual learning

Learning where to learn - Gradient sparsity in meta and continual learning In this paper, we investigate gradient sparsity found by MAML in various co

Johannes Oswald 28 Dec 09, 2022
Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.

Robotic Arm Simulation in ROS2 and Gazebo General Overview This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZE

David Valencia 12 Jan 02, 2023
Image Super-Resolution Using Very Deep Residual Channel Attention Networks

Image Super-Resolution Using Very Deep Residual Channel Attention Networks

kongdebug 14 Oct 14, 2022
这是一个unet-pytorch的源码,可以训练自己的模型

Unet:U-Net: Convolutional Networks for Biomedical Image Segmentation目标检测模型在Pytorch当中的实现 目录 性能情况 Performance 所需环境 Environment 注意事项 Attention 文件下载 Downl

Bubbliiiing 567 Jan 05, 2023
Using NumPy to solve the equations of fluid mechanics together with Finite Differences, explicit time stepping and Chorin's Projection methods

Computational Fluid Dynamics in Python Using NumPy to solve the equations of fluid mechanics 🌊 🌊 🌊 together with Finite Differences, explicit time

Felix Köhler 4 Nov 12, 2022
PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System

PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System

Libo Qin 25 Sep 06, 2022
Lightweight Face Image Quality Assessment

LightQNet This is a demo code of training and testing [LightQNet] using Tensorflow. Uncertainty Losses: IDQ loss PCNet loss Uncertainty Networks: Mobi

Kaen 5 Nov 18, 2022
Model-based reinforcement learning in TensorFlow

Bellman Website | Twitter | Documentation (latest) What does Bellman do? Bellman is a package for model-based reinforcement learning (MBRL) in Python,

46 Nov 09, 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks

This package requires jax, tensorflow, and numpy. Either tensorflow or scikit-learn can be used for loading data. To run in a nix-shell with required

Felix Biggs 0 Feb 04, 2022
Scripts and misc. stuff related to the PortSwigger Web Academy

PortSwigger Web Academy Notes Mostly scripts to automate the exploits. Going in the order of the recomended learning path - starting with SQLi. Commun

pageinsec 17 Dec 30, 2022
Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization

Hybrid solving process for combinatorial optimization problems Combinatorial optimization has found applications in numerous fields, from aerospace to

117 Dec 13, 2022
Official repository for "Action-Based Conversations Dataset: A Corpus for Building More In-Depth Task-Oriented Dialogue Systems"

Action-Based Conversations Dataset (ABCD) This respository contains the code and data for ABCD (Chen et al., 2021) Introduction Whereas existing goal-

ASAPP Research 49 Oct 09, 2022
Evaluating saliency methods on artificial data with different background types

Evaluating saliency methods on artificial data with different background types This repository contains the relevant code for the MedNeurips 2021 subm

2 Jul 05, 2022
This is the official PyTorch implementation of the paper "TransFG: A Transformer Architecture for Fine-grained Recognition" (Ju He, Jie-Neng Chen, Shuai Liu, Adam Kortylewski, Cheng Yang, Yutong Bai, Changhu Wang, Alan Yuille).

TransFG: A Transformer Architecture for Fine-grained Recognition Official PyTorch code for the paper: TransFG: A Transformer Architecture for Fine-gra

Ju He 307 Jan 03, 2023
Visualizing lattice vibration information from phonon dispersion to atoms (For GPUMD)

Phonon-Vibration-Viewer (For GPUMD) Visualizing lattice vibration information from phonon dispersion for primitive atoms. In this tutorial, we will in

Liangting 6 Dec 10, 2022
Style transfer, deep learning, feature transform

FastPhotoStyle License Copyright (C) 2018 NVIDIA Corporation. All rights reserved. Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons

NVIDIA Corporation 10.9k Jan 02, 2023
A PyTorch implementation of Radio Transformer Networks from the paper "An Introduction to Deep Learning for the Physical Layer".

An Introduction to Deep Learning for the Physical Layer An usable PyTorch implementation of the noisy autoencoder infrastructure in the paper "An Intr

Gram.AI 120 Nov 21, 2022