cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.12077952
title: Rewired SSCx network model with 2nd-order simplified connectome

description: This dataset is an accompanying dataset to the article with the title "A connectome manipulation framework for the systematic and reproducible study of structure-function relationships through simulations" (DOI: 10.1162/netn_a_00429). The dataset is part of the main accompanying dataset (DOI: 10.5281/zenodo.11402579) and contains the rewired SSCx network model with simplified E-to-E connectivity within the central column based on a 2nd-order simplified model of connectivity which had been fit against the original connectome beforehand.

The corresponding repository with code, configuration files, and detailed instructions for reproducing the results in this dataset as well as generating the results figures in the accompanying article is available here: https://github.com/BlueBrain/sscx-connectome-manipulations

The underlying Connectome-Manipulator software is available here: https://github.com/BlueBrain/connectome-manipulator

Additional requirement: Original SSCx network model (DOI: 10.5281/zenodo.8026353)

ℹ️ Disclaimer: Some results may have been produced with an older version of Connectome-Manipulator, so slight differences might be possible when re-running with the latest version.



Funding

Funding provided by the Swiss government’s ETH Board to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL).
description: SSCx-simplified-connectome-order2.xz



SSCx-HexO1-Release__ConnRewireOrder2Hex0EE ... Rewired SSCx network model with 2nd-order simplified connectome in SONATA format

SSCx-HexO1-Release__ConnRewireOrder2Hex0EE__calib-<N>__/logs/ ... Log files of Nth estimation run for matching overall numbers of connections with the original connectome
description: Uncompress: tar -xf <filename>.xz

Download and uncompress the original network model (DOI: 10.5281/zenodo.8026353)

EITHER: Replace edges.h5 from the original SSCx network model by extracted edges.h5 file

OR: Adjust the respective path references in circuit_config<_tc>.json from the extracted circuit pointing to the folder location of the original SSCx network model
DOI: 10.5281/zenodo.12077954
title: Rewired SSCx network model with 2nd-order simplified connectome

description: This dataset is an accompanying dataset to the article with the title "A connectome manipulation framework for the systematic and reproducible study of structure-function relationships through simulations" (DOI: 10.1162/netn_a_00429). The dataset is part of the main accompanying dataset (DOI: 10.5281/zenodo.11402579) and contains the rewired SSCx network model with simplified E-to-E connectivity within the central column based on a 2nd-order simplified model of connectivity which had been fit against the original connectome beforehand.

The corresponding repository with code, configuration files, and detailed instructions for reproducing the results in this dataset as well as generating the results figures in the accompanying article is available here: https://github.com/BlueBrain/sscx-connectome-manipulations

The underlying Connectome-Manipulator software is available here: https://github.com/BlueBrain/connectome-manipulator

Additional requirement: Original SSCx network model (DOI: 10.5281/zenodo.8026353)

ℹ️ Disclaimer: Some results may have been produced with an older version of Connectome-Manipulator, so slight differences might be possible when re-running with the latest version.



Funding

Funding provided by the Swiss government’s ETH Board to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL).
description: SSCx-simplified-connectome-order2.xz



SSCx-HexO1-Release__ConnRewireOrder2Hex0EE ... Rewired SSCx network model with 2nd-order simplified connectome in SONATA format

SSCx-HexO1-Release__ConnRewireOrder2Hex0EE__calib-<N>__/logs/ ... Log files of Nth estimation run for matching overall numbers of connections with the original connectome
description: Uncompress: tar -xf <filename>.xz

Download and uncompress the original network model (DOI: 10.5281/zenodo.8026353)

EITHER: Replace edges.h5 from the original SSCx network model by extracted edges.h5 file

OR: Adjust the respective path references in circuit_config<_tc>.json from the extracted circuit pointing to the folder location of the original SSCx network model
DOI: 10.57702/wxvylc0f
title: Houston HI, Samson HI, Jasper Ridge HI

description: Houston HI, Samson HI, Jasper Ridge HI
DOI: 10.57702/q6u1dlxg
title: BraTS 2020 training, validation and test datasets

description: The dataset contains features extracted from the 213 ground truth images for OS prediction.
DOI: 10.57702/wlxh2auv
title: MTTN: Multi-Pair Text to Text Narratives for Prompt Generation

description: A large-scale dataset for generating prompts that can be used in diffusion models for text-to-text generation tasks.
DOI: 10.57702/lydv1ylk
title: Microsoft COCO: common objects in context

description: The COCO dataset is a large-scale dataset for object detection and image classification.
DOI: 10.57702/gjvr2zfc
title: WIT: Wikipedia-based image text dataset for multimodal multilingual machine learning

description: A multimodal dataset for machine learning tasks, focusing on Wikipedia-based image text datasets.
DOI: 10.57702/xtar17ow
title: Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models

description: A dataset for multimodal learning tasks, focusing on region-to-phrase correspondences for image-to-sentence models.
DOI: 10.57702/ikobwovp
title: USDA Crop Dataset and HRRR Computed Dataset

description: The USDA Crop Dataset and HRRR Computed Dataset are used for predicting crop yields at the county level across the United States.
DOI: 10.57702/wdz077co
title: USDA Crop Dataset

description: The USDA Crop Dataset provides annual crop data for major crops grown in the United States on a county-level basis.
DOI: 10.15468/dl.b34g38
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "TaxonKey is Combretum mkuzense J.D.Carr & Retief"
 ]
}

 The dataset includes 43 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014188-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/g6hk2yw6
title: VIGOR: Cross-View Image Geo-localization beyond One-to-one Retrieval

description: A new large-scale benchmark for cross-view image geo-localization beyond one-to-one retrieval, which is a more realistic setting for real-world applications.
DOI: 10.57702/arncao2d
title: Retinal Cross-Domain Dataset

description: A retinal cross-domain dataset consisting of 1,179 OCT volumes (57,771 B-scans after re-sampling Cirrus OCTs) with a total of 11,172 B-scans (66 Heidelberg Spectralis and 162 Zeiss Cirrus volumes).
DOI: 10.57702/7063f2d9
title: Retinal Fluid Segmentation Dataset

description: A dataset of 228 OCT volumes with a total of 11,172 B-scans (66 Heidelberg Spectralis and 162 Zeiss Cirrus volumes).
DOI: 10.57702/tbcbtzrz
title: MSLUB dataset

description: The MSLUB dataset consists of brain MRI scans of 30 patients with multiple sclerosis.
DOI: 10.57702/2sv8nt6v
title: DOTA, HRSC2016, DIOR-R, UCAS-AOD, ICDAR2015, ICDAR2017 MLT, MSRA-TD500, FDDB

description: The dataset used in the paper for 2-D and 3-D object detection, including aerial images, scene text, and face detection.
DOI: 10.57702/ivi88loe
title: KITTI, Waymo Open Dataset

description: The dataset used in the paper for 2-D and 3-D object detection, including aerial images, scene text, and face detection.
DOI: 10.57702/8pdsiq9d
title: Convallaria 1

description: The dataset used for training and testing the N2V2 method, consisting of 100 noisy short exposure fluorescence acquisitions of the same 1024 × 1024px field of view of the same sample.
DOI: 10.57702/i2xuh3tc
title: SoccerNet

description: SoccerNet is a dataset for action spotting in soccer videos, containing a large number of annotated videos.
DOI: 10.5281/zenodo.12078722
title: Rewired SSCx network model with 3rd-order simplified connectome

description: This dataset is an accompanying dataset to the article with the title "A connectome manipulation framework for the systematic and reproducible study of structure-function relationships through simulations" (DOI: 10.1162/netn_a_00429). The dataset is part of the main accompanying dataset (DOI: 10.5281/zenodo.11402579) and contains the rewired SSCx network model with simplified E-to-E connectivity within the central column based on a 3rd-order simplified model of connectivity which had been fit against the original connectome beforehand.

The corresponding repository with code, configuration files, and detailed instructions for reproducing the results in this dataset as well as generating the results figures in the accompanying article is available here: https://github.com/BlueBrain/sscx-connectome-manipulations

The underlying Connectome-Manipulator software is available here: https://github.com/BlueBrain/connectome-manipulator

Additional requirement: Original SSCx network model (DOI: 10.5281/zenodo.8026353)

ℹ️ Disclaimer: Some results may have been produced with an older version of Connectome-Manipulator, so slight differences might be possible when re-running with the latest version.



Funding

Funding provided by the Swiss government’s ETH Board to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL).
description: SSCx-simplified-connectome-order3.xz



SSCx-HexO1-Release__ConnRewireOrder3Hex0EE ... Rewired SSCx network model with 3rd-order simplified connectome in SONATA format

SSCx-HexO1-Release__ConnRewireOrder3Hex0EE__calib-<N>__/logs/ ... Log files of Nth estimation run for matching overall numbers of connections with the original connectome
description: Uncompress: tar -xf <filename>.xz

Download and uncompress the original network model (DOI: 10.5281/zenodo.8026353)

EITHER: Replace edges.h5 from the original SSCx network model by extracted edges.h5 file

OR: Adjust the respective path references in circuit_config<_tc>.json from the extracted circuit pointing to the folder location of the original SSCx network model
DOI: 10.5281/zenodo.12078723
title: Rewired SSCx network model with 3rd-order simplified connectome

description: This dataset is an accompanying dataset to the article with the title "A connectome manipulation framework for the systematic and reproducible study of structure-function relationships through simulations" (DOI: 10.1162/netn_a_00429). The dataset is part of the main accompanying dataset (DOI: 10.5281/zenodo.11402579) and contains the rewired SSCx network model with simplified E-to-E connectivity within the central column based on a 3rd-order simplified model of connectivity which had been fit against the original connectome beforehand.

The corresponding repository with code, configuration files, and detailed instructions for reproducing the results in this dataset as well as generating the results figures in the accompanying article is available here: https://github.com/BlueBrain/sscx-connectome-manipulations

The underlying Connectome-Manipulator software is available here: https://github.com/BlueBrain/connectome-manipulator

Additional requirement: Original SSCx network model (DOI: 10.5281/zenodo.8026353)

ℹ️ Disclaimer: Some results may have been produced with an older version of Connectome-Manipulator, so slight differences might be possible when re-running with the latest version.



Funding

Funding provided by the Swiss government’s ETH Board to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL).
description: SSCx-simplified-connectome-order3.xz



SSCx-HexO1-Release__ConnRewireOrder3Hex0EE ... Rewired SSCx network model with 3rd-order simplified connectome in SONATA format

SSCx-HexO1-Release__ConnRewireOrder3Hex0EE__calib-<N>__/logs/ ... Log files of Nth estimation run for matching overall numbers of connections with the original connectome
description: Uncompress: tar -xf <filename>.xz

Download and uncompress the original network model (DOI: 10.5281/zenodo.8026353)

EITHER: Replace edges.h5 from the original SSCx network model by extracted edges.h5 file

OR: Adjust the respective path references in circuit_config<_tc>.json from the extracted circuit pointing to the folder location of the original SSCx network model
DOI: 10.57702/ezwk103u
title: Myanmar video sequence

description: Myanmar video sequence, which was obtained from a publicly available video database.
DOI: 10.57702/5djalbtw
title: Stocks

description: Time series imputation is one of the most fundamental tasks for time series. Real-world time series datasets are frequently incomplete (or irregular with missing observations), in which case imputation is strongly required.
DOI: 10.57702/ry4wmbih
title: Electricity

description: Time series imputation is one of the most fundamental tasks for time series. Real-world time series datasets are frequently incomplete (or irregular with missing observations), in which case imputation is strongly required.
DOI: 10.57702/jf6m9g2e
title: Energy

description: Time series imputation is one of the most fundamental tasks for time series. Real-world time series datasets are frequently incomplete (or irregular with missing observations), in which case imputation is strongly required.
DOI: 10.57702/d5rh2c80
title: Trafﬁc4cast 2021 - Temporal and Spatial Few-Shot Transfer Learning in Trafﬁc Map Movie Forecasting

description: The dataset provided for the two tasks consists of 10 different cities from around the world over the course of 2 years. The cities have been split into 3 categories: Core Challenge, Extended Challenge and Additional Training.
DOI: 10.57702/vywssxnv
title: High Speed and High Dynamic Range Video with an Event Camera

description: The dataset used for high speed and high dynamic range video with an event camera.
DOI: 10.57702/4cir7vbn
title: Detection of Traﬃc Signs in Real-World Images: The German Traﬃc Sign Detection Benchmark

description: The dataset used for detection of traﬃc signs in real-world images.
DOI: 10.57702/wabvhshs
title: Fast Image Reconstruction with an Event Camera

description: The dataset used for fast image reconstruction with an event camera.
DOI: 10.57702/acq7tfa5
title: Mask Synthesis Dataset

description: The dataset used for mask synthesis consists of 10000 images generated based on the strategies: symmetry, simplicity, and aspect ratio.
DOI: 10.57702/bg5p51j6
title: 2D energy function

description: The dataset used in the paper is a 2D energy function, which is a mixture of Gaussian distributions.
DOI: 10.57702/xuzfjm8l
title: Molecular system dataset

description: The dataset used in the paper is a molecular system dataset, which is used to predict equilibrium distributions.
DOI: 10.57702/bo4xy1bt
title: ClinicalLab: A Comprehensive Clinical Diagnosis Agent Alignment Suite

description: Large language models (LLMs) have achieved significant performance progress in various natural language processing applications. However, LLMs still struggle to meet the strict requirements for accuracy and reliability in the medical field and face many challenges in clinical applications. Existing clinical diagnostic evaluation benchmarks for evaluating medical agents powered by LLMs have severe limitations. Firstly, most existing medical evaluation benchmarks face the risk of data leakage or contamination. Secondly, existing benchmarks often neglect the characteristics of multiple departments and specializations in modern medical practice. Thirdly, existing evaluation methods are limited to multiple-choice questions, which do not align with the real-world diagnostic scenarios. Lastly, existing evaluation methods lack comprehensive evaluations of end-to-end real clinical scenarios. These limitations in benchmarks in turn obstruct advancements of LLMs and agents for medicine. To address these limitations, we introduce ClinicalLab, a comprehensive clinical diagnosis agent alignment suite, including ClinicalBench, ClinicalMetrics, and ClinicalAgent, to promote development of clinical diagnostic agents.
DOI: 10.57702/mn1sb61a
title: Remote PPG

description: The remote PPG dataset contains remote PPG signals extracted from face videos.
DOI: 10.57702/o44vcb94
title: ThermoPore: Predicting Part Porosity Based on Thermal Images Using Deep Learning

description: Thermal images of Laser Powder Bed Fusion fabricated samples utilizing in-situ thermal image monitoring data.
DOI: 10.5281/zenodo.12080631
title: Rewired SSCx network model with 4th-order simplified connectome

description: This dataset is an accompanying dataset to the article with the title "A connectome manipulation framework for the systematic and reproducible study of structure-function relationships through simulations" (DOI: 10.1162/netn_a_00429). The dataset is part of the main accompanying dataset (DOI: 10.5281/zenodo.11402579) and contains the rewired SSCx network model with simplified E-to-E connectivity within the central column based on a 4th-order simplified model of connectivity which had been fit against the original connectome beforehand.

The corresponding repository with code, configuration files, and detailed instructions for reproducing the results in this dataset as well as generating the results figures in the accompanying article is available here: https://github.com/BlueBrain/sscx-connectome-manipulations

The underlying Connectome-Manipulator software is available here: https://github.com/BlueBrain/connectome-manipulator

Additional requirement: Original SSCx network model (DOI: 10.5281/zenodo.8026353)

ℹ️ Disclaimer: Some results may have been produced with an older version of Connectome-Manipulator, so slight differences might be possible when re-running with the latest version.



Funding

Funding provided by the Swiss government’s ETH Board to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL).
description: SSCx-simplified-connectome-order4.xz



SSCx-HexO1-Release__ConnRewireOrder4Hex0EE ... Rewired SSCx network model with 4th-order simplified connectome in SONATA format

SSCx-HexO1-Release__ConnRewireOrder4Hex0EE__calib-<N>__/logs/ ... Log files of Nth estimation run for matching overall numbers of connections with the original connectome
description: Uncompress: tar -xf <filename>.xz

Download and uncompress the original network model (DOI: 10.5281/zenodo.8026353)

EITHER: Replace edges.h5 from the original SSCx network model by extracted edges.h5 file

OR: Adjust the respective path references in circuit_config<_tc>.json from the extracted circuit pointing to the folder location of the original SSCx network model
DOI: 10.5281/zenodo.12080632
title: Rewired SSCx network model with 4th-order simplified connectome

description: This dataset is an accompanying dataset to the article with the title "A connectome manipulation framework for the systematic and reproducible study of structure-function relationships through simulations" (DOI: 10.1162/netn_a_00429). The dataset is part of the main accompanying dataset (DOI: 10.5281/zenodo.11402579) and contains the rewired SSCx network model with simplified E-to-E connectivity within the central column based on a 4th-order simplified model of connectivity which had been fit against the original connectome beforehand.

The corresponding repository with code, configuration files, and detailed instructions for reproducing the results in this dataset as well as generating the results figures in the accompanying article is available here: https://github.com/BlueBrain/sscx-connectome-manipulations

The underlying Connectome-Manipulator software is available here: https://github.com/BlueBrain/connectome-manipulator

Additional requirement: Original SSCx network model (DOI: 10.5281/zenodo.8026353)

ℹ️ Disclaimer: Some results may have been produced with an older version of Connectome-Manipulator, so slight differences might be possible when re-running with the latest version.



Funding

Funding provided by the Swiss government’s ETH Board to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL).
description: SSCx-simplified-connectome-order4.xz



SSCx-HexO1-Release__ConnRewireOrder4Hex0EE ... Rewired SSCx network model with 4th-order simplified connectome in SONATA format

SSCx-HexO1-Release__ConnRewireOrder4Hex0EE__calib-<N>__/logs/ ... Log files of Nth estimation run for matching overall numbers of connections with the original connectome
description: Uncompress: tar -xf <filename>.xz

Download and uncompress the original network model (DOI: 10.5281/zenodo.8026353)

EITHER: Replace edges.h5 from the original SSCx network model by extracted edges.h5 file

OR: Adjust the respective path references in circuit_config<_tc>.json from the extracted circuit pointing to the folder location of the original SSCx network model
DOI: 10.57702/q1a3zotj
title: nuScenes: A multimodal dataset for autonomous driving

description: nuScenes: A multimodal dataset for autonomous driving.
DOI: 10.57702/tgzceeph
title: BraTS 2021

description: Multi-parametric MRI scans from 2000 patients were used for BraTS2021, 1251 of which were provided with segmentation labels to the participants for developing their algorithms, 219 of which were used for the public leaderboard during the validation phase, and the remaining 530 cases were intended for the private leaderboard and the final ranking of the participants.
DOI: 10.57702/rhjxxnj7
title: Fine-Art Paintings Dataset

description: The fine-art paintings dataset consists of about 45,500 training images and 19,500 testing images.
DOI: 10.57702/pri2uksy
title: WMT datasets

description: WMT datasets are large-scale machine translation datasets.
DOI: 10.57702/2w4mj8iq
title: Laion-400M

description: Text-to-image Latent Diffusion model, CLIP model, Blended Diffusion model, GLIDE model, GLIDE-filtered model
DOI: 10.57702/po4xlf0a
title: UCI datasets

description: The dataset used in the paper is a set of UCI datasets, including adult, census, covertype, financial, joke, mushroom, and statlog.
DOI: 10.57702/clz8l3fh
title: SMMix: Self-Motivated Image Mixing for Vision Transformers

description: CutMix is a vital augmentation strategy that determines the performance and generalization ability of vision transformers (ViTs). However, the inconsistency between the mixed images and the corresponding labels harms its effectiveness. Existing CutMix variants tackle this problem by generating more consistent mixed images or more precise mixed labels, but inevitably introduce heavy training overhead or require extra information, undermining ease of use.
DOI: 10.57702/6qvfy7h6
title: D1Q3 Lattice Boltzmann simulations of the coupled FitzHugh-Nagumo PDEs

description: The dataset generated by D1Q3 Lattice Boltzmann simulations of the coupled FitzHugh-Nagumo PDEs.
DOI: 10.57702/tx67qeur
title: LiqD: A Dynamic Liquid Level Detection Model

description: A container dynamic liquid level detection model based on U²-Net.
DOI: 10.57702/dg8rf2if
title: UCR Time Series Classiﬁcation Archive

description: Time series classiﬁcation has recently received a lot of attention over the past three decades. Such data is widely available everywhere and collected with various sensors.