Results 1 to 10 of about 16,036,271 (117)
Distilling Causal Effect of Data in Class-Incremental Learning [PDF]
Computer Vision and Pattern Recognition, 2021 We propose a causal framework to explain the catastrophic forgetting in Class-Incremental Learning (CIL) and then derive a novel distillation method that is orthogonal to the existing anti-forgetting techniques, such as data replay and feature/label ...
Xinting Hu +4 more
semanticscholar +1 more source
Data-Driven Causal Effect Estimation Based on Graphical Causal Modelling: A Survey [PDF]
ACM Computing Surveys, 2022 In many fields of scientific research and real-world applications, unbiased estimation of causal effects from non-experimental data is crucial for understanding the mechanism underlying the data and for decision-making on effective responses or ...
De-Bo Cheng +4 more
semanticscholar +1 more source
Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction [PDF]
Conference on Computational Natural Language Learning, 2021 When language models process syntactically complex sentences, do they use their representations of syntax in a manner that is consistent with the grammar of the language? We propose AlterRep, an intervention-based method to address this question. For any
Shauli Ravfogel +3 more
semanticscholar +1 more source
Applying the adjustment set to estimate causal effect of data based on the causal graph model
Sichuan jingshen weisheng, 2022 The purpose of this paper was to introduce the five limitations of the PROC CAUSALGRAPH procedure and estimate the causal effect of the data by using the adjustment set based on the causal graph model.
Hu Chunyan, Hu Liangping
doaj +1 more source
Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters [PDF]
INFORMS Journal on Data Science, 2021 Causal decision making (CDM) at scale has become a routine part of business, and increasingly, CDM is based on statistical models and machine learning algorithms.
Carlos Fernández-Loría, F. Provost
semanticscholar +1 more source
Quantifying Causal Path-Specific Importance in Structural Causal Model
Computation, 2023 Path-specific effect analysis is a powerful tool in causal inference. This paper provides a definition of causal counterfactual path-specific importance score for the structural causal model (SCM). Different from existing path-specific effect definitions,
Xiaoxiao Wang +5 more
doaj +1 more source
Causal Effect Identification in Cluster DAGs [PDF]
AAAI Conference on Artificial Intelligence, 2022 Reasoning about the effect of interventions and counterfactuals is a fundamental task found throughout the data sciences. A collection of principles, algorithms, and tools has been developed for performing such tasks in the last decades.
T. Anand +3 more
semanticscholar +1 more source
Enhanced causal effect of ecosystem photosynthesis on respiration during heatwaves
Science Advances, 2023 Because of global warming, Earth’s ecosystems have been experiencing more frequent and severe heatwaves. Heatwaves are expected to tip terrestrial carbon sequestration by elevating ecosystem respiration and suppressing gross primary productivity (GPP ...
Jiaye Ping +8 more
semanticscholar +1 more source
Frontiers in Psychiatry, 2023 BackgroundMental disorders, characterized as products of biopsychosocial interactions, have emerged as a leading contributor to the worldwide rise in overall morbidity and disability rates.
Menglin He +3 more
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Frontiers in Immunology, 2023 BackgroundAn association between Graves’ disease (GD) and the gut microbiome has been identified, but the causal effect between them remains unclear.MethodsBidirectional two-sample Mendelian randomization (MR) analysis was used to detect the causal ...
Jiamin Cao +8 more
doaj +1 more source