• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 205 matches

• 2021
• 
  Kun Qiu, Qin Zhang:
  The M-DUCG Methodology to Calculate the Joint Probability Distribution of Directed Cycle Graph With Local Data and Domain Causal Knowledge. IEEE Access 9: 36087-36099 (2021)
• 
  Hyoung Seok Shin, Allan Jeong:
  Modeling the relationship between students' prior knowledge, causal reasoning processes, and quality of causal maps. Comput. Educ. 163: 104113 (2021)
• 
  Xiaojun Ma, Takeshi Imai, Emiko Y. Shinohara, Satoshi Kasai, Kosuke Kato, Rina Kagawa, Kazuhiko Ohe:
  EHR2CCAS: A framework for mapping EHR to disease knowledge presenting causal chain of disorders - chronic kidney disease example. J. Biomed. Informatics 115: 103692 (2021)
• 
  Maël Le Treust, Matthieu R. Bloch:
  State Leakage and Coordination With Causal State Knowledge at the Encoder. IEEE Trans. Inf. Theory 67(2): 805-823 (2021)
• 
  Anthony C. Constantinou, Norman E. Fenton, Martin Neil:
  How do some Bayesian Network machine learned graphs compare to causal knowledge? CoRR abs/2101.10461 (2021)
• 
  Trent Kyono, Ioana Bica, Zhaozhi Qian, Mihaela van der Schaar:
  Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge. CoRR abs/2102.06271 (2021)
• 
  Zijian Wang, Hao Wang, Xiangfeng Luo, Jianqi Gao:
  Back to Prior Knowledge: Joint Event Causality Extraction via Convolutional Semantic Infusion. CoRR abs/2102.09923 (2021)
• 
  Takeshi Teshima, Masashi Sugiyama:
  Incorporating Causal Graphical Prior Knowledge into Predictive Modeling via Simple Data Augmentation. CoRR abs/2103.00136 (2021)
• 2020
• 
  Yunpu Ma:
  Learning with relational knowledge in the context of cognition, quantum computing, and causality. Ludwig Maximilian University of Munich, Germany, 2020
• 
  Wei Wang, Gangqiang Hu, Bo Yuan, Shandong Ye, Chao Chen, YaYun Cui, Xi Zhang, Liting Qian:
  Prior-Knowledge-Driven Local Causal Structure Learning and Its Application on Causal Discovery Between Type 2 Diabetes and Bone Mineral Density. IEEE Access 8: 108798-108810 (2020)
• 
  Nasrin Kalanat, Alireza Khanshan, Eynollah Khanjari:
  Actionable knowledge discovery from social networks using causal structures of structural features. J. Intell. Fuzzy Syst. 39(1): 489-501 (2020)
• 
  Li Li, Yongfang Xie, Xiaofang Chen, Weichao Yue, Zhaohui Zeng:
  Dynamic uncertain causality graph based on cloud model theory for knowledge representation and reasoning. Int. J. Mach. Learn. Cybern. 11(8): 1781-1799 (2020)
• 
  Philipp Kuhnke, Marie C. Beaupain, Vincent K. M. Cheung, Konstantin Weise, Markus Kiefer, Gesa Hartwigsen:
  Left posterior inferior parietal cortex causally supports the retrieval of action knowledge. NeuroImage 219: 117041 (2020)
• 
  Oktie Hassanzadeh, Debarun Bhattacharjya, Mark Feblowitz, Kavitha Srinivas, Michael Perrone, Shirin Sohrabi, Michael Katz:
  Causal Knowledge Extraction through Large-Scale Text Mining. AAAI 2020: 13610-13611
• 
  Bryan Andrews:
  On the Completeness of Causal Discovery in the Presence of Latent Confounding with Tiered Background Knowledge. AISTATS 2020: 4002-4011
• 
  Xinyu Zuo, Yubo Chen, Kang Liu, Jun Zhao:
  KnowDis: Knowledge Enhanced Data Augmentation for Event Causality Detection via Distant Supervision. COLING 2020: 1544-1550
• 
  Hengyi Hu, Larry Kerschberg:
  Capturing Causal Knowledge from Authoritative Medical Ontologies. COMPSAC 2020: 1373-1378
• 
  Eva Blomqvist, Marjan Alirezaie, Marina Santini:
  Towards Causal Knowledge Graphs - Position Paper. KDH@ECAI 2020: 58-62
• 
  Noah Weber, Rachel Rudinger, Benjamin Van Durme:
  Causal Inference of Script Knowledge. EMNLP (1) 2020: 7583-7596
• 
  Genki Yamashita, Taro Kanno, Kazuo Furuta:
  Interactive Method to Elicit Local Causal Knowledge for Creating a Huge Causal Network. HCI (37) 2020: 437-446
• 
  Johannes Huegle, Christopher Hagedorn, Matthias Uflacker:
  How Causal Structural Knowledge Adds Decision-Support in Monitoring of Automotive Body Shop Assembly Lines. IJCAI 2020: 5246-5248
• 
  Jian Liu, Yubo Chen, Jun Zhao:
  Knowledge Enhanced Event Causality Identification with Mention Masking Generalizations. IJCAI 2020: 3608-3614
• 
  Christopher Frye, Colin Rowat, Ilya Feige:
  Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability. NeurIPS 2020
• 
  Tom Heskes, Evi Sijben, Ioan Gabriel Bucur, Tom Claassen:
  Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models. NeurIPS 2020
• 
  Amir-Hossein Karimi, Bodo Julius von Kügelgen, Bernhard Schölkopf, Isabel Valera:
  Algorithmic recourse under imperfect causal knowledge: a probabilistic approach. NeurIPS 2020
• 
  Hong Qing Yu:
  Extracting and Representing Causal Knowledge of Health Condition. BIRDS@SIGIR 2020: 70-78
• 
  Yangyi Lu, Amirhossein Meisami, Ambuj Tewari, William Yan:
  Regret Analysis of Bandit Problems with Causal Background Knowledge. UAI 2020: 141-150
• 
  Noah Weber, Rachel Rudinger, Benjamin Van Durme:
  Causal Inference of Script Knowledge. CoRR abs/2004.01174 (2020)
• 
  Amir-Hossein Karimi, Julius von Kügelgen, Bernhard Schölkopf, Isabel Valera:
  Algorithmic recourse under imperfect causal knowledge: a probabilistic approach. CoRR abs/2006.06831 (2020)
• 
  Victor Zitian Chen, Felipe Montano-Campos, Wlodek Zadrozny:
  Causal Knowledge Extraction from Scholarly Papers in Social Sciences. CoRR abs/2006.08904 (2020)

skipping 175 more matches