Results 11 to 20 of about 42,084,791 (333)
The “Problem” of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2022 Human variation in labeling is often considered noise. Annotation projects for machine learning (ML) aim at minimizing human label variation, with the assumption to maximize data quality and in turn optimize and maximize machine learning metrics. However,
Barbara Plank
semanticscholar +1 more source
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling [PDF]
Knowledge Discovery and Data Mining, 2021 Vast amount of data generated from networks of sensors, wearables, and the Internet of Things (IoT) devices underscores the need for advanced modeling techniques that leverage the spatio-temporal structure of decentralized data due to the need for edge ...
Chuizheng Meng +2 more
semanticscholar +1 more source
Bayesian synthesis of probabilistic programs for automatic data modeling [PDF]
Proc. ACM Program. Lang., 2019 We present new techniques for automatically constructing probabilistic programs for data analysis, interpretation, and prediction. These techniques work with probabilistic domain-specific data modeling languages that capture key properties of a broad ...
Feras A. Saad +4 more
semanticscholar +1 more source
Neural Networks-Based Aerodynamic Data Modeling: A Comprehensive Review
IEEE Access, 2020 This paper reviews studies on neural networks in aerodynamic data modeling. In this paper, we analyze the shortcomings of computational fluid dynamics (CFD) and traditional reduced-order models (ROMs).
Liwei Hu +3 more
semanticscholar +1 more source
Robust Estimation for Semi-Functional Linear Model with Autoregressive Errors
Mathematics, 2023 It is well-known that the traditional functional regression model is mainly based on the least square or likelihood method. These methods usually rely on some strong assumptions, such as error independence and normality, that are not always satisfied ...
Bin Yang +3 more
doaj +1 more source
Deep Generative Modeling of LiDAR Data [PDF]
, 2019 Building models capable of generating structured output is a key challenge for AI and robotics. While generative models have been explored on many types of data, little work has been done on synthesizing lidar scans, which play a key role in robot ...
Caccia, Lucas +3 more
core +2 more sources
Non-Markovian data-driven modeling of single-cell motility [PDF]
, 2020 Trajectories of human breast cancer cells moving on one-dimensional circular tracks are modeled by thenon-Markovian version of the Langevin equation that includes an arbitrary memory function.
Daldrop, Jan O. +4 more
core +1 more source
Mathematics, 2022 Various approaches including hypothesis test and confidence interval (CI) construction have been proposed to assess non-inferiority and assay sensitivity via a known fraction or pre-specified margin in three-arm trials with continuous or discrete ...
Niansheng Tang, Fan Liang
doaj +1 more source
Southern Europe and western Asian marine heatwaves (SEWA-MHWs): a dataset based on macroevents [PDF]
Earth System Science Data, 2023 Marine heatwaves (MHWs) induce significant impacts on marine ecosystems. There is a growing need for knowledge about extreme climate events to better inform decision-makers on future climate-related risks.
G. Bonino +4 more
doaj +1 more source
Data in Business Process Models. A Preliminary Empirical Study [PDF]
, 2015 Traditional activity-centric process modeling languages treat data as simple black boxes acting as input or output for activities. Many alternate and emerging process modeling paradigms, such as case handling and artifact-centric process modeling, give ...
Andrews, Kevin +5 more
core +1 more source