cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10823655
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Ernst Bresslau, http://www.wikidata.org/entity/Q1226497. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q1226497
DOI: 10.5281/zenodo.14262913
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Ernst Bresslau, http://www.wikidata.org/entity/Q1226497. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q1226497
DOI: 10.57702/vrgtuhrw
title: RIM-ONE-r3 Dataset

description: The RIM-ONE-r3 dataset contains 60 test images.
DOI: 10.57702/m16c6gw8
title: CIFAR-10, CIFAR-100, and STL-10 datasets

description: The dataset used in the paper is not explicitly described, but it is mentioned that the authors used CIFAR-10, CIFAR-100, and STL-10 datasets for training and testing the embedding functions.
DOI: 10.57702/jmh3y7i7
title: TinyImagenet dataset

description: The dataset used in the paper is not explicitly described, but it is mentioned that the authors used TinyImagenet dataset for pre-training the embedding functions.
DOI: 10.57702/2vwfx36r
title: The movielens datasets: History and context

description: The Movielens-100k dataset is a large-scale movie recommendation dataset.
DOI: 10.57702/g7bq0n4e
title: Intact-VAE: Estimating Treatment Effects under Unobserved Confounding

description: Intact-VAE: Estimating Treatment Effects under Unobserved Confounding
DOI: 10.57702/x2emv1w2
title: Pokec dataset

description: The Pokec dataset is a social network dataset.
DOI: 10.5281/zenodo.14246646
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Patrick Browne, http://www.wikidata.org/entity/Q15480. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q15480
DOI: 10.5281/zenodo.14246647
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Patrick Browne, http://www.wikidata.org/entity/Q15480. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q15480
DOI: 10.5281/zenodo.14262915
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Patrick Browne, http://www.wikidata.org/entity/Q15480. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q15480
DOI: 10.57702/anqkdozx
title: Multi-scale OOD DEtection (MODE)

description: Out-of-distribution (OOD) detection aims to detect “unknown” data whose labels have not been seen during the in-distribution (ID) training process.
DOI: 10.57702/tio34pjl
title: OOD datasets

description: The datasets used for OOD detection.
DOI: 10.57702/poxzqkh6
title: SceneNet RGB-D

description: The dataset used in this paper for multi-sensor next-best-view planning as matroid-constrained submodular maximization.
DOI: 10.57702/q3e8ynew
title: Davis dataset for video object segmentation

description: The Davis dataset is a benchmark for video object segmentation. It contains 30 videos with 40 frames each.
DOI: 10.57702/7wsbpe2t
title: ResNetX: a more disordered and deeper network architecture

description: Image classification results on CIFAR-10 and CIFAR-100 benchmarks suggested that our new network architecture performs better than ResNet.
DOI: 10.57702/v4d06jp1
title: Indifference Pricing of Pure Endowments in a Markov-Modulated Market Model

description: The dataset used in this paper is a stochastic-factor model for an insurance company with exponential utility preferences.
DOI: 10.57702/miy2gkq9
title: Physionet 2016 dataset

description: The Physionet 2016 dataset is a collection of heart sound recordings used for heart sound classification.
DOI: 10.57702/u3f55v3f
title: MyStyle++: A Controllable Personalized Generative Prior

description: The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a few images of an individual with a set of corresponding attributes.
DOI: 10.5281/zenodo.10472365
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Nikolai Samsonov, http://www.wikidata.org/entity/Q12371074. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q12371074
DOI: 10.5281/zenodo.8103274
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Nikolai Samsonov, http://www.wikidata.org/entity/Q12371074. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q12371074
DOI: 10.57702/x0xxew5x
title: Leela’s corpus

description: The dataset contains word order frequencies from Leela’s corpus, which are used as a proxy for cognitive cost.
DOI: 10.5281/zenodo.14262918
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Nikolai Samsonov, http://www.wikidata.org/entity/Q12371074. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q12371074
DOI: 10.5281/zenodo.8103273
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Nikolai Samsonov, http://www.wikidata.org/entity/Q12371074. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q12371074
DOI: 10.57702/gkkdavdq
title: QuickDraw

description: QuickDraw dataset contains hand-drawn sketches
DOI: 10.57702/ry6mmk9y
title: ET3D dataset

description: The dataset used in the paper for text-to-3D generation, consisting of 5,000 different prompts and 800,000 generated images.
DOI: 10.57702/yg1hwk8s
title: LLFF-T

description: The dataset used in the paper is a large-scale paired dataset for training a NeRF-agnostic restorer. It consists of 8 different forward-facing scenes with 20-62 high-quality input views.
DOI: 10.57702/yipws2pq
title: Noisy LLFF Synthetic

description: The dataset used in the paper is a large-scale paired dataset for training a NeRF-agnostic restorer. It consists of 8 virtual scenes, each with 400 images.
DOI: 10.57702/szzdpvft
title: Foursquare Singapore (SIN) dataset

description: The SIN dataset is a collection of 194,108 check-ins made within Singapore from 2,321 users at 5,596 POIs between Aug. 2010 and Jul. 2011.
DOI: 10.57702/ft68c45k
title: CA dataset

description: The CA dataset is a collection of 483,813 check-ins made in Foursquare by 4,163 users living in California.
DOI: 10.57702/9fpgjste
title: Latent Diffusion Models for Structural Component Design

description: The dataset employed for training and validation comprises pairs of initial conditions and corresponding ground truth: designs optimized using the Solid Isotropic Material with Penalization (SIMP) method.
DOI: 10.57702/9lzt0qzn
title: Group-Attention Single-Shot Detector (GA-SSD) dataset

description: A dataset for pulmonary nodule detection with 4146 CT scans and 8 categories of pulmonary nodules.
DOI: 10.57702/hz5h1y5k
title: Daily Data of Eighty-Eight Stocks

description: The dataset used in this research is the daily data of eighty-eight stocks.
DOI: 10.57702/grz1rji6
title: TinyTracker: Ultra-Fast and Ultra-Low-Power Edge Vision In-Sensor for Gaze Estimation

description: TinyTracker is a highly efcient, fully quantized model for 2D gaze estimation designed to maximize the performance of the edge vision systems considered in this study.
DOI: 10.57702/7k4jzky1
title: Eye tracking for everyone

description: Eye tracking for everyone
DOI: 10.57702/ksys5323
title: Learning-by-synthesis for appearance-based 3D gaze estimation

description: Learning-by-synthesis for appearance-based 3D gaze estimation
DOI: 10.57702/a1z3g4x2
title: PatchComplete dataset

description: The dataset used in this paper for 3D shape completion from partial scans.
DOI: 10.57702/ftenjlve
title: 3DPW

description: 3D human pose and mesh estimation, the task of recon-structing human pose in 3D space given a 2D image of the person, is an ill-posed problem, and many data-driven ap-proaches using deep learning were recently proposed (Liu, Kortylewski, and Yuille 2023; Gholami et al. 2022a; Li et al. 2022). A dataset covering the distribution of possible human poses, global orientation, appearance, and other attributes would be large and difficult to capture in practice.
DOI: 10.3886/e198401v1-160181
title: From boom to bust: real commodity prices from 1850

description: This is the annual update of Jacks, D.S. (2019), “From Boom to Bust: A Typology of Real Commodity Prices in the Long Run.” Cliometrica 13(2), 201-220. It analyses an accompanying dataset on 42 commodities, comprising 7.43 trillion USD worth of production in 2019 and spanning the years from 1850 to 2023. It also presents evidence on three commodity price indices using various weighting schemes for the period from 1900 to 2023. Applying weights drawn from the value of production in 1975, real commodity prices are estimated to have increased by 41.13% (or 0.28% per annum) from 1900, 47.42% (or 0.53% per annum) from 1950, and 16.01% (or 0.31% per annum) from 1975. The data also indicates the presence of three complete commodity price cycles, entailing multi-year positive deviations from the long-run trend. The most recently completed cycle began in 1996, reached its peak in 2010, and is now near its trough.
DOI: 10.57702/dw5d2ygh
title: Flickr

description: The dataset used in the paper is a multi-graph problem, where each graph represents a different network. The dataset is used to evaluate the performance of the RECS algorithm on multi-label classification tasks.
DOI: 10.57702/9vi7yzpb
title: Toy Dataset

description: A 2-dimensional toy dataset used to illustrate the performance-interpretability dilemma in single-subject decoding.
DOI: 10.3886/e198401
title: From boom to bust: real commodity prices from 1850

description: This is the annual update of Jacks, D.S. (2019), “From Boom to Bust: A Typology of Real Commodity Prices in the Long Run.” Cliometrica 13(2), 201-220. It analyses an accompanying dataset on 42 commodities, comprising 7.43 trillion USD worth of production in 2019 and spanning the years from 1850 to 2023. It also presents evidence on three commodity price indices using various weighting schemes for the period from 1900 to 2023. Applying weights drawn from the value of production in 1975, real commodity prices are estimated to have increased by 41.13% (or 0.28% per annum) from 1900, 47.42% (or 0.53% per annum) from 1950, and 16.01% (or 0.31% per annum) from 1975. The data also indicates the presence of three complete commodity price cycles, entailing multi-year positive deviations from the long-run trend. The most recently completed cycle began in 1996, reached its peak in 2010, and is now near its trough.
DOI: 10.3886/e198401v1-160182
title: From boom to bust: real commodity prices from 1850

description: This is the annual update of Jacks, D.S. (2019), “From Boom to Bust: A Typology of Real Commodity Prices in the Long Run.” Cliometrica 13(2), 201-220. It analyses an accompanying dataset on 42 commodities, comprising 7.43 trillion USD worth of production in 2019 and spanning the years from 1850 to 2023. It also presents evidence on three commodity price indices using various weighting schemes for the period from 1900 to 2023. Applying weights drawn from the value of production in 1975, real commodity prices are estimated to have increased by 41.13% (or 0.28% per annum) from 1900, 47.42% (or 0.53% per annum) from 1950, and 16.01% (or 0.31% per annum) from 1975. The data also indicates the presence of three complete commodity price cycles, entailing multi-year positive deviations from the long-run trend. The most recently completed cycle began in 1996, reached its peak in 2010, and is now near its trough.
DOI: 10.57702/jc13a779
title: MPEG 8i Dataset

description: The MPEG 8i dataset contains 6 voxelized point cloud models.
DOI: 10.57702/j4nm2o69
title: Facescape: A Large-Scale High-Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction

description: Facescape: A large-scale high-quality 3D face dataset and detailed riggable 3D face prediction.
DOI: 10.57702/qdm5s4nk
title: XNLI

description: The XNLI dataset comprises pairs of sentences with a label categorizing the semantic relationship between the two sentences into one of three classifications: entailment, contradiction, or neutral.
DOI: 10.57702/02gidcrs
title: Diffusion-EXR: Controllable Review Generation for Explainable Recommendation via Diffusion Models

description: Diffusion-EXR is evaluated on two publicly available datasets on e-commerce and hotel recommendation, i.e.,Amazon-Clothing Shoes and Jewellery (Amazon-CSJ) and TripAd-visor.
DOI: 10.57702/aqlc471v
title: Amazon-Clothing Shoes and Jewellery (Amazon-CSJ)

description: Amazon-CSJ contains 38,764 users and 22,919 items while TripAdvisor has 9,765 users and 6,280 items.
DOI: 10.57702/adpica13
title: Learning to Disentangle Scenes for Person Re-identiﬁcation

description: The proposed method employs a divide-and-conquer strategy for the ReID task. Concretely, two self-supervision operations are used to generate new images with the characteristics of occluded and scale variation scenes.
DOI: 10.57702/vt3cp1hm
title: Market1501

description: Re-identiﬁcation (Re-ID) problems aim to determine corresponding targets across multiple cameras or different locations in the same camera from the gallery set with a given probe.
DOI: 10.57702/8ic1qhni
title: P-DukeMTMC-reID

description: The P-DukeMTMC-reID benchmark contains 12927 images of 665 person identities for training, including 2647 images with occlusion and 10280 images without occlusion.
DOI: 10.57702/7p008l24
title: Protein Crystallization Image Dataset

description: The dataset used in this work consisted of 486,000 protein crystallography X-ray images.
DOI: 10.57702/njzfpm63
title: CrystalNet Dataset

description: The dataset introduced in [17] and [18] was used to evaluate the performance of CrystalNet.
DOI: 10.57702/kou4oyvk
title: Habitat-Matterport 3D Dataset (HM3D)

description: The HM3D dataset is a large-scale 3D environment dataset, consisting of 1000 large-scale 3D environments for embodied AI. The dataset is used to evaluate the performance of SLAM algorithms in complex environments.
DOI: 10.57702/b1slktys
title: LiDAR and Floor Plan Dataset

description: The dataset used in this paper is a collection of LiDAR images and floor plans, used to evaluate the performance of the proposed SLAM algorithm.
DOI: 10.57702/9tcsuoex
title: MovieLens

description: The dataset is a movie review dataset with five types of nodes (movie, director, tag, writer, and user) and four types of edges (movie-director relation, movie-tag relation, movie-writer relation, and movie-user relation).
DOI: 10.57702/njzjkdtv
title: Modcloth

description: This dataset is used to evaluate the performance of the proposed DeCA and DeCA(p) methods.
DOI: 10.5281/zenodo.14230333
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Lucas M. Carbone, https://orcid.org/0000-0002-2571-5905. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.5281/zenodo.14230334
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Lucas M. Carbone, https://orcid.org/0000-0002-2571-5905. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.5281/zenodo.14262923
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Lucas M. Carbone, https://orcid.org/0000-0002-2571-5905. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.57702/0apcvh74
title: Adressa

description: This dataset is used to evaluate the performance of the proposed DeCA and DeCA(p) methods.
DOI: 10.57702/afrwxtoz
title: Very Deep Multilingual Convolutional Neural Networks for LVCSR

description: Convolutional neural networks (CNNs) are a standard component of many current state-of-the-art Large Vocabulary Continuous Speech Recognition (LVCSR) systems. However, CNNs in LVCSR have not kept pace with recent advances in other domains where deeper neural networks provide superior performance.
DOI: 10.57702/ilc7bqoj
title: FLIR, KAIST, and InfraPlane datasets

description: The dataset used in the paper is FLIR, KAIST, and InfraPlane datasets for infrared target detection.
DOI: 10.5281/zenodo.13967747
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Leopold III of Belgium, http://www.wikidata.org/entity/Q12973. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q12973
DOI: 10.5281/zenodo.14262925
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Leopold III of Belgium, http://www.wikidata.org/entity/Q12973. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q12973
DOI: 10.5281/zenodo.8147863
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Leopold III of Belgium, http://www.wikidata.org/entity/Q12973. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q12973
DOI: 10.57702/nep0kka3
title: Sheikh Shakhbout Medical City
DOI: 10.57702/59nshdnq
title: SAM-VMNet: Deep Neural Networks For Coronary Angiography Vessel Segmentation

description: Coronary artery disease (CAD) is one of the most prevalent diseases in the cardiovascular field and one of the major contributors to death worldwide. Computed Tomography Angiography (CTA) images are regarded as the authoritative standard for the diagnosis of coronary artery disease, and by performing vessel segmentation and stenosis detection on CTA images, physicians are able to diagnose coronary artery disease more accurately.
DOI: 10.57702/46406ddv
title: Concentration measurements commencing after immediate exposure

description: The dataset used in the paper is a simulation of a cell measuring concentration and gradient of chemoattractants.
DOI: 10.5281/zenodo.10440347
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Elizabeth M. Browne, http://www.wikidata.org/entity/Q124026009. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q124026009
DOI: 10.5281/zenodo.10449734
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Elizabeth M. Browne, http://www.wikidata.org/entity/Q124026009. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q124026009
DOI: 10.5281/zenodo.10440346
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Elizabeth M. Browne, http://www.wikidata.org/entity/Q124026009. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q124026009
DOI: 10.5281/zenodo.14262929
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Elizabeth M. Browne, http://www.wikidata.org/entity/Q124026009. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q124026009
DOI: 10.57702/ieuyd7aq
title: Latent Diffusion Model for Conditional Reservoir Facies Generation

description: Creating accurate and geologically realistic reservoir facies based on limited measurements is crucial for field development and reservoir management, especially in the oil and gas sector.
DOI: 10.57702/373pfrgv
title: DABNet for Real-time Semantic Segmentation

description: The proposed Depth-wise Asymmetric Bottleneck Network (DABNet) is designed for real-time semantic segmentation. It uses a novel Depth-wise Asymmetric Bottleneck (DAB) module to extract local and contextual features jointly.
DOI: 10.57702/eextq63i
title: Font dataset

description: The dataset used in the paper is a collection of unpaired shapes, including chairs and tables, and letters in different font styles.
DOI: 10.57702/qo5wbplm
title: RainBench

description: A large-scale radar echo dataset for precipitation prediction, constructed to address the scarcity of meteorological data in the domain of spatiotemporal prediction.
DOI: 10.57702/xe6nmlpo
title: RNN/LSTM with modified Adam optimizer for automobile spare parts demand forecasting

description: A dataset for automobile spare parts demand forecasting, using RNN/LSTM with modified Adam optimizer.
DOI: 10.57702/fudverdl
title: Actions as space-time shapes

description: A dataset for action recognition, using spatio-temporal features.
DOI: 10.57702/8pi8zwzv
title: TinyImageNet

description: The dataset used for the experiments of the paper "CORE-PERIPHERY PRINCIPLE GUIDED REDISIGN OF SELF-ATTENTION IN TRANSFORMERS"
DOI: 10.57702/p5143m9c
title: lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systems

description: Latent factor analysis via dynamical systems (LFADS) is an RNN-based variational sequential autoencoder that achieves state-of-the-art performance in denoising high-dimensional neural activity for downstream applications in science and engineering.