Learning Bayesian Networks: The Combination of Knowledge and Statistical Data

27 February 2013

Papers citing "Learning Bayesian Networks: The Combination of Knowledge and Statistical Data"

50 / 366 papers shown

Title
Exploiting Noise as a Resource for Computation and Learning in Spiking Neural Networks Gehua (Marcus) Ma Rui Yan Huajin Tang 24 21 0 25 May 2023
Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning Chi Han Qizheng He Charles Yu Xinya Du Hanghang Tong Heng Ji 18 13 0 22 May 2023
Open problems in causal structure learning: A case study of COVID-19 in the UK Anthony C. Constantinou N. K. Kitson Yang Liu Kiattikun Chobtham Arian Hashemzadeh Praharsh Nanavati R. Mbuvha Bruno Petrungaro CML 21 9 0 05 May 2023
On Learning Time Series Summary DAGs: A Frequency Domain Approach Aramayis Dallakyan CML AI4TS 19 3 0 17 Apr 2023
Sequential Linearithmic Time Optimal Unimodal Fitting When Minimizing Univariate Linear Losses Kaan Gokcesu Hakan Gokcesu 11 0 0 04 Apr 2023
Informed Machine Learning, Centrality, CNN, Relevant Document Detection, Repatriation of Indigenous Human Remains M. A. Bashar R. Nayak G. Knapman Paul Turnbull C. Fforde 23 1 0 25 Mar 2023
Causal Discovery from Temporal Data: An Overview and New Perspectives Chang Gong Di Yao Chuzhe Zhang Wenbin Li Jingping Bi AI4TS CML 16 17 0 17 Mar 2023
An Approximate Bayesian Approach to Covariate-dependent Graphical Modeling Sutanoy Dasgupta P. Zhao Jacob Helwig P. Ghosh D. Pati Bani Mallick 15 1 0 15 Mar 2023
BCSSN: Bi-direction Compact Spatial Separable Network for Collision Avoidance in Autonomous Driving Haichuan Li Liguo Zhou Alois C. Knoll 11 0 0 12 Mar 2023
Learning interpretable causal networks from very large datasets, application to 400,000 medical records of breast cancer patients M. Ribeiro-Dantas Honghao Li Vincent Cabeli Louise Dupuis Franck Simon Liza Hettal A. Hamy Hervé Isambert CML 9 8 0 11 Mar 2023
Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting An Zhang Fang Liu Wenchang Ma Zhibo Cai Xiang Wang Tat-Seng Chua CML 24 5 0 06 Mar 2023
Neural Graph Revealers H. Shrivastava Urszula Chajewska BDL 31 6 0 27 Feb 2023
Bayesian Networks for Named Entity Prediction in Programming Community Question Answering Alexey Gorbatovski Sergey Kovalchuk 9 2 0 26 Feb 2023
Bayesian Structure Scores for Probabilistic Circuits Yang Yang G. Gala Robert Peharz TPM 11 7 0 23 Feb 2023
Copula-based transferable models for synthetic population generation Pascal Jutras-Dubé Mohammad B. Al-Khasawneh Zhichao Yang Javier Bas Fabian Bastin C. Cirillo 11 3 0 17 Feb 2023
A Survey on Causal Reinforcement Learning Yan Zeng Ruichu Cai Fuchun Sun Libo Huang Z. Hao CML 26 27 0 10 Feb 2023
GFlowNets for AI-Driven Scientific Discovery Moksh Jain T. Deleu Jason S. Hartford Cheng-Hao Liu Alex Hernandez-Garcia Yoshua Bengio AI4CE 21 45 0 01 Feb 2023
Evaluating Temporal Observation-Based Causal Discovery Techniques Applied to Road Driver Behaviour Rhys Howard Lars Kunze CML 21 7 0 31 Jan 2023
Deep Causal Learning for Robotic Intelligence Y. Li CML 17 5 0 23 Dec 2022
A Comprehensively Improved Hybrid Algorithm for Learning Bayesian Networks: Multiple Compound Memory Erasing Baokui Mou BDL 17 1 0 05 Dec 2022
Directed Acyclic Graph Structure Learning from Dynamic Graphs Shaohua Fan Shuyang Zhang Xiao Wang Chuan Shi CML 31 5 0 30 Nov 2022
A Short Survey of Systematic Generalization Yuanpeng Li AI4CE 22 1 0 22 Nov 2022
Methods for Recovering Conditional Independence Graphs: A Survey H. Shrivastava Urszula Chajewska CML 22 11 0 13 Nov 2022
Learning Latent Structural Causal Models Jithendaraa Subramanian Yashas Annadani Ivaxi Sheth Nan Rosemary Ke T. Deleu Stefan Bauer Derek Nowrouzezahrai Samira Ebrahimi Kahou CML 22 7 0 24 Oct 2022
GFlowCausal: Generative Flow Networks for Causal Discovery Wenqian Li Yinchuan Li Shengyu Zhu Yunfeng Shao Jianye Hao Yan Pang BDL CML 11 12 0 15 Oct 2022
Neural Graphical Models H. Shrivastava Urszula Chajewska 25 10 0 02 Oct 2022
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 53 78 0 16 Sep 2022
On the Sparse DAG Structure Learning Based on Adaptive Lasso Danru Xu Erdun Gao Wei Huang Menghan Wang Andy Song Mingming Gong CML 8 4 0 07 Sep 2022
Learning Multiscale Non-stationary Causal Structures Gabriele DÁcunto G. D. F. Morales P. Bajardi Francesco Bonchi CML AI4TS 32 3 0 31 Aug 2022
Domain Knowledge in A*-Based Causal Discovery Steven Kleinegesse A. Lawrence Hana Chockler CML 16 3 0 17 Aug 2022
Multiscale Causal Structure Learning Gabriele DÁcunto P. Lorenzo Sergio Barbarossa 45 4 0 16 Jul 2022
The Impact of Variable Ordering on Bayesian Network Structure Learning N. K. Kitson Anthony C. Constantinou CML 15 9 0 17 Jun 2022
Using Mixed-Effects Models to Learn Bayesian Networks from Related Data Sets M. Scutari Christopher Marquis Laura Azzimonti 18 4 0 08 Jun 2022
Causality Learning With Wasserstein Generative Adversarial Networks H. Petkov Colin Hanley Feng Dong CML GAN OOD 12 0 0 03 Jun 2022
Structure Learning for Hybrid Bayesian Networks Wanchuang Zhu Ngoc Lan Chi Nguyen 22 1 0 03 Jun 2022
A Log-Linear Time Sequential Optimal Calibration Algorithm for Quantized Isotonic L2 Regression Kaan Gokcesu Hakan Gokcesu 14 1 0 01 Jun 2022
Differentiable Invariant Causal Discovery Yu-Xiang Wang An Zhang Xiang Wang Yancheng Yuan Xiangnan He Tat-Seng Chua OOD CML 22 1 0 31 May 2022
Amortized Inference for Causal Structure Learning Lars Lorch Scott Sussex Jonas Rothfuss Andreas Krause Bernhard Schölkopf CML 15 60 0 25 May 2022
Digital Twin for Secure Semiconductor Lifecycle Management: Prospects and Applications Hasan Al Shaikh Mohammad Bin Monjil Shi-Xuan Chen Navid Asadizanjani Farimah Farahmandi M. Tehranipoor Fahim Rahman 6 2 0 22 May 2022
Adversarial random forests for density estimation and generative modeling David S. Watson Kristin Blesch Jan Kapar Marvin N. Wright GAN 57 19 0 19 May 2022
Learning Multitask Gaussian Bayesian Networks Shuai Liu Yixuan Qiu Baojuan Li Huaning Wang Xiangyu Chang 6 2 0 11 May 2022
Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications Marcel Wienöbst Max Bannach Maciej Liskiewicz 19 9 0 05 May 2022
From Statistical to Causal Learning Bernhard Schölkopf Julius von Kügelgen CML 20 45 0 01 Apr 2022
DAG-WGAN: Causal Structure Learning With Wasserstein Generative Adversarial Networks H. Petkov Colin Hanley Feng Dong GAN OOD CML 25 6 0 01 Apr 2022
Quantum Approximate Optimization Algorithm for Bayesian network structure learning Vicente P. Soloviev C. Bielza P. Larrañaga 11 11 0 04 Mar 2022
Differentiable Causal Discovery Under Latent Interventions Gonccalo R. A. Faria André F. T. Martins Mário A. T. Figueiredo BDL CML OOD 32 22 0 04 Mar 2022
Bayesian Structure Learning with Generative Flow Networks T. Deleu António Góis Chris C. Emezue M. Rankawat Simon Lacoste-Julien Stefan Bauer Yoshua Bengio BDL 34 143 0 28 Feb 2022
Parallel Sampling for Efficient High-dimensional Bayesian Network Structure Learning Zhi-gao Guo Anthony C. Constantinou TPM 14 0 0 19 Feb 2022
Surf or sleep? Understanding the influence of bedtime patterns on campus Teng Guo Linhong Li Dongyu Zhang Feng Xia 19 2 0 18 Feb 2022
BCDAG: An R package for Bayesian structure and Causal learning of Gaussian DAGs F. Castelletti Alessandro Mascaro CML 17 3 0 28 Jan 2022