Results 31 to 40 of about 574 (203)

Simulating Counterfactuals

Journal of Artificial Intelligence Research
Counterfactual 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, Vihola Matti, Tikka Santtu   +2 more
openaire   +3 more sources

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
doaj   +1 more source

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
doaj   +1 more source

Counterfactual worlds [PDF]

, 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
openaire   +4 more sources

Mechanistically Interpretable Artificial Intelligence for Designing Oxygen Electrocatalysts

Advanced Materials, EarlyView.
Mechanistically interpretable artificial intelligence screens nearly seven million perovskite compositions and identifies key descriptors—d‐p hybridization and densification resistance—that govern oxygen electrocatalysis. The discovered BaCo0.8Nb0.1Zr0.1O3‐δ achieves a record 2.68 W cm−2 peak power density at 600°C with over 500 h of durable operation ...
Xueyu Hu, Yucun Zhou, Haoyu Li, Zheyu Luo, Nai Shi, Yong Ding, Weining Wang, Weilin Zhang, Doyeub Kim, Chanho Kim, Yoojin Ahn, Nikhil Govindarajan, Minda Zou, Zhijun Liu, Yuefeng Song, Meilin Liu   +15 more
wiley   +1 more source

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, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +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, Joshua R. Loftus, Julia Stoyanovich   +2 more
openaire   +2 more sources

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, Zexi Chen, Yuanxiang Miao, Zuolin Shen, Deyu Cai, Shijie Tang, Yun Xue, Weifeng Guo, Hongbin Ji, Jian Liu, Kazuyuki Aihara, Luonan Chen   +11 more
wiley   +1 more source

ORBIT‐AMD: Ordinal Risk, Bilateral Imaging, and Trajectory Learning for Age‐Related Macular Degeneration in Multi‐Cohorts

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, Dejia Wen, Patrick Yu‐Wai‐Man, Xiaorong Li   +3 more
wiley   +1 more source

Livestock Multi‐Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation

Advanced Science, EarlyView.
A three‐tier livestock multi‐omics framework resolves four typical analytical pitfalls. Moving from statistical association through machine learning preprocessing to triple‐modal causal inference, it converts omics results into genomic selection and gene editing strategies to achieve One Health, underpinned by multi‐omics data, multimodal sequencing ...
Jiying Wen, Zhongyu Wang, Jieping Huang, Fen Li, Ningbo Chen, Yun Ma   +5 more
wiley   +1 more source