Results 11 to 20 of about 596,618 (263)
Assessing Generalizability of CodeBERT
2021 IEEE International Conference on Software Maintenance and Evolution (ICSME), 2021 Pre-trained models like BERT have achieved strong improvements on many natural language processing (NLP) tasks, showing their great generalizability. The success of pre-trained models in NLP inspires pre-trained models for programming language. Recently, CodeBERT, a model for both natural language (NL) and programming language (PL), pre-trained on code
Xin Zhou 0014 +2 more
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European Journal of Psychotraumatology, 2020 Background The International Trauma Questionnaire (ITQ) is a self-report measure for post-traumatic stress disorder (PTSD) and complex post-traumatic stress disorder (CPTSD), corresponding to the diagnostic criteria in the International Classification of
Peter Sele +3 more
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Generalizability of Subgroup Effects
Epidemiology, 2021 Generalizability methods are increasingly used to make inferences about the effect of interventions in target populations using a study sample. Most existing methods to generalize effects from sample to population rely on the assumption that subgroup-specific effects generalize directly.
Seamans, Marissa +4 more
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One for More: Selecting Generalizable Samples for Generalizable ReID Model
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 Current training objectives of existing person Re-IDentification (ReID) models only ensure that the loss of the model decreases on selected training batch, with no regards to the performance on samples outside the batch. It will inevitably cause the model to over-fit the data in the dominant position (e.g., head data in imbalanced class, easy samples ...
Enwei Zhang +9 more
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Generalizing Experimental Findings
Journal of Causal Inference, 2015 This note examines one of the most crucial questions in causal inference: “How generalizable are randomized clinical trials?” The question has received a formal treatment recently, using a non-parametric setting, and has led to a simple and general ...
Pearl Judea
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Reverse-Net: Few-Shot Learning with Reverse Teaching for Deformable Medical Image Registration
Applied Sciences, 2023 Multimodal medical image registration has an important role in monitoring tumor growth, radiotherapy, and disease diagnosis. Deep-learning-based methods have made great progress in the past few years.
Xin Zhang +3 more
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Data from Investigating Variation in Replicability: A “Many Labs” Replication Project
Journal of Open Psychology Data, 2014 This dataset is from the Many Labs Replication Project in which 13 effects were replicated across 36 samples and over 6,000 participants. Data from the replications are included, along with demographic variables about the participants and contextual ...
Richard A. Klein +50 more
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Behavioral and Brain Sciences, 2019 Most theories and hypotheses in psychology are verbal in nature, yet their evaluation overwhelmingly relies on inferential statistical procedures. The validity of the move from qualitative to quantitative analysis depends on the verbal and statistical expressions of a hypothesis being closely aligned—that is, that the two must refer to roughly the same
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Frontiers in Behavioral Neuroscience, 2023 The low replicability of scientific studies has become an important issue. One possible cause is low representativeness of the experimental design employed.
Enrique Hernández-Arteaga, Anders Ågmo
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Neurology, 2012 Clinical and epidemiologic investigations are paying increasing attention to the critical constructs of "representativeness" of study samples and "generalizability" of study results. This is a laudable trend and yet, these key concepts are often misconstrued and conflated, masking the central issues of internal and external validity. The authors define
Walter A, Kukull, Mary, Ganguli
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