Results 31 to 40 of about 4,402 (251)
Journal of Artificial Intelligence ResearchCounterfactual inference considers a hypothetical intervention in a parallel world that shares some evidence with the factual world. If the evidence specifies a conditional distribution on a manifold, counterfactuals may be analytically intractable. We present an algorithm for simulating values from a counterfactual distribution where conditions can be
Karvanen Juha +2 more
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Counterfactuals: The Epistemic Analysis
Philosophia Scientiæ, 2005 Ordinarily counterfactuals are seen as making statements about states of affairs, albeit ones that hold in merely possible or alternative worlds. Thus analyzed, nearly all counterfactuals turn out to be incoherent.
John-Michael Kuczynski
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Narrative Quantum Cosmology in Michael Frayn’s Copenhagen
American, British and Canadian Studies Journal, 2021 Twentieth-century drama has made the stage a site for reflecting on science. Michael Frayn’s Copenhagen, considered by many as one of the most striking contributions to “science plays,” portrays the elusive yet crucial short meeting of the two pillars of
Amani Omid, Pirnajmuddin Hossein
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Clinical Impact of NOTCH3 Variant Location After First Stroke in CADASIL
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Despite its monogenic origin, Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy exhibits marked variability in clinical expression and severity. Variants in the NOTCH3 gene, within epidermal growth factor‐like repeat domains 1–6 or 7–34, are known to influence disease onset, but their impact ...
Léa Aguilhon +5 more
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Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Advanced Science, EarlyView.Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Counterfactuals for the Future
Proceedings of the AAAI Conference on Artificial Intelligence, 2023 Counterfactuals are often described as 'retrospective,' focusing on hypothetical alternatives to a realized past. This description relates to an often implicit assumption about the structure and stability of exogenous variables in the system being modeled --- an assumption that is reasonable in many settings where counterfactuals are used. In this work,
Lucius E. J. Bynum +2 more
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Advanced Science, EarlyView.This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
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CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning
Advanced Science, EarlyView.CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang +11 more
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, 2015 We study a generalization of the treatment effect model in which an observed discrete classifier indicates in which one of a set of counterfactual processes a decision maker is observed. The other observed outcomes are delivered by the particular counterfactual process in which the decision maker is found.
Andrew Chesher, Adam Rosen
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Advanced Science, EarlyView.Eligibility flow and real‐world AMD burden in the UKB retinal imaging cohort and TMUEH external‐validation cohort. Overview of the ORBIT‐AMD architecture, integrating retinal representation pretraining, bilateral eye‐graph modeling and concept bottleneck learning to support ordered risk, bilateral context, interpretable lesion concepts, longitudinal ...
Xuehao Cui +3 more
wiley +1 more source