1. A Generalized Bias-Variance Decomposition for Bregman Divergences
   2025/11/11 by David Pfau, Pfau, David · 1 voice · 3 citations
   Computer Science · Physics and Astronomy · #Bregman divergence #Decomposition #Estimation theory #Exponential family #Exponential function #Gaussian Processes and Bayesian Inference #Generalization #Maximum likelihood #Statistical Mechanics and Entropy #Stochastic Gradient Optimization Techniques #Type (biology)
2. Gravitational-Wave Parameter Estimation in non-Gaussian noise using Score-Based Likelihood Characterization
   2024/10/25 by Ronan Legin, M. Isi, Legin, Ronan +7 · 4 citations
   Economics, Econometrics and Finance · Mathematics · Physics and Astronomy · #Acoustics #Advanced Frequency and Time Standards #Algorithm #Artificial intelligence #Astrophysics #Characterization (materials science) #Complex Systems and Time Series Analysis #Computer science #FOS: Physical sciences #Gaussian #Gaussian noise #General Relativity and Quantum Cosmology (gr-qc) #Gravitational wave #High Energy Astrophysical Phenomena (astro-ph.HE) #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Mathematics #Maximum likelihood #Noise (video) #Optics #Physics #Statistical physics #Statistics
3. Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks Using the Marginal Likelihood
   2024/02/25 by Rayen Dhahri, Dhahri, Rayen, Alexander Immer +7 · 2 voices · 4 citations
   Computer Science · Mathematics · #Artificial intelligence #Bayesian network #Bayesian probability #Computer science #Marginal likelihood #Mathematics #Maximum likelihood #Neural Networks and Applications #Occam's razor #Programming language #Statistics #occam
4. Maximum Likelihood Degrees of Brownian Motion Tree Models: Star Trees and Root Invariance
   2024/02/15 by Jane Ivy Coons, Shelby Cox, Coons, Jane Ivy +5 · 1 citation
   Economics, Econometrics and Finance · Mathematics · #14M25 #62F10 #62R01 #Algebraic Geometry (math.AG) #Brownian motion #Complex Systems and Time Series Analysis #Computer science #Diffusion process #FOS: Biological sciences #FOS: Mathematics #Geometric Brownian motion #Mathematical analysis #Mathematics #Maximum likelihood #Physics #Populations and Evolution (q-bio.PE) #Root (linguistics) #Star (game theory) #Statistical physics #Statistics #Statistics Theory (math.ST) #Stochastic processes and statistical mechanics #Tree (set theory)
5. Blind Channel Estimation and Joint Symbol Detection with Data-Driven Factor Graphs
   2024/01/23 by Luca Schmid, Schmid, Luca, Tomer Raviv +5 · 2 citations
   Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Advanced biosensing and bioanalysis techniques #Algorithm #Belief propagation #Channel (broadcasting) #Computation #Computational complexity theory #Computer science #Decoding methods #Detector #Expectation–maximization algorithm #FOS: Computer and information sciences #FOS: Electrical engineering #Factor graph #Graph #Information Theory (cs.IT) #Machine Learning (cs.LG) #Mathematical optimization #Mathematics #Maximization #Maximum likelihood #RNA and protein synthesis mechanisms #Signal Processing (eess.SP) #Statistics #Symbol (formal) #Telecommunications #Theoretical computer science #Wireless Signal Modulation Classification #electronic engineering #information engineering
6. Kernel Density Estimation for Multiclass Quantification
   2023/12/31 by Alejandro Moreo, Moreo, Alejandro, Pablo González +3 · 5 citations
   Computer Science · Mathematics · #Artificial intelligence #Bayesian Methods and Mixture Models #Class (philosophy) #Computer science #Data mining #Density estimation #Estimator #Expectation–maximization algorithm #FOS: Computer and information sciences #Histogram #Image (mathematics) #Kernel (algebra) #Kernel density estimation #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine learning #Matching (statistics) #Mathematical optimization #Mathematics #Maximization #Maximum likelihood #Multivariate statistics #Pattern recognition (psychology) #Representation (politics) #Statistics
7. Should We Learn Most Likely Functions or Parameters?
   2023/11/27 by Shikai Qiu, Qiu, Shikai, Tim G. J. Rudner +5 · 3 citations
   Computer Science · Engineering · Mathematics · Medicine · #A priori and a posteriori #AI in cancer detection #Algorithm #Applied mathematics #Artificial intelligence #Artificial neural network #Bayesian probability #Computer science #Estimation theory #FOS: Computer and information sciences #Function (biology) #Generalization #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mathematical analysis #Mathematical optimization #Mathematics #Maxima and minima #Maximum a posteriori estimation #Maximum likelihood #Medical Imaging and Analysis #Overfitting #Parameter space #Posterior probability #Radiomics and Machine Learning in Medical Imaging #Robustness (evolution) #Statistics
8. Joint channel estimation and data detection in massive MIMO systems based on diffusion models
   2023/11/17 by Nicolás Zilberstein, Zilberstein, Nicolas, Ananthram Swami +3 · 11 citations
   Computer Science · Engineering · Mathematics · #A priori and a posteriori #Advanced MIMO Systems Optimization #Algorithm #Bayesian Methods and Mixture Models #Blind Source Separation Techniques #Channel (broadcasting) #Computer science #Diffusion #Engineering #FOS: Electrical engineering #Joint (building) #Joint probability distribution #Mathematical optimization #Mathematics #Maximum a posteriori estimation #Maximum likelihood #Overhead (engineering) #Process (computing) #Sampling (signal processing) #Signal Processing (eess.SP) #Statistics #Telecommunications #electronic engineering #information engineering
9. StepMix: A Python Package for Pseudo-Likelihood Estimation of Generalized Mixture Models with External Variables
   2023/04/07 by Sacha Morin, Morin, Sacha, Robin Legault +10 · 2 citations
   Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Computer science #Covariate #Econometrics #Estimator #Expectation–maximization algorithm #FOS: Computer and information sciences #Interpretability #Latent class model #Latent variable #Latent variable model #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine learning #Mathematics #Maximum likelihood #Methodology (stat.ME) #Python (programming language) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistical model #Statistics #Structural equation modeling #Subroutine
10. Regression model selection via log‐likelihood ratio and constrained minimum criterion
    2023/01/10 by Min Tsao · 1 citation
    Mathematics · #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Advanced Statistical Methods and Models #Akaike information criterion #Bayesian information criterion #Likelihood-ratio test #Statistics #Deviance information criterion #Model selection #Mathematics #Frequentist inference #Information Criteria #Likelihood principle #Sample size determination #Score test #Regression analysis #Selection (genetic algorithm) #Ratio test #Bayesian probability #Likelihood function #Maximum likelihood #Bayesian inference #Computer science #Artificial intelligence #Quasi-maximum likelihood
11. Maximum Likelihood Estimation for Semiparametric Regression Models with Interval-Censored Multi-State Data
    2022/09/16 by Yu Gu, Gu, Yu, Donglin Zeng +5 · 3 citations
    Mathematics · #Applied mathematics #Censoring (clinical trials) #Covariance matrix #Covariate #Econometrics #Estimator #Expectation–maximization algorithm #Interval (graph theory) #Mathematics #Maximum likelihood #Nonparametric statistics #Semiparametric model #Semiparametric regression #Statistical Distribution Estimation and Applications #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics
12. As Little as Possible, as Much as Necessary: Detecting Over- and Undertranslations with Contrastive Conditioning
    2022/03/03 by Jannis Vamvas, Vamvas, Jannis, Rico Sennrich +1 · 2 citations
    Computer Science · Mathematics · #Artificial intelligence #Computation and Language (cs.CL) #Computer science #FOS: Computer and information sciences #Machine learning #Machine translation #Mathematics #Maximum likelihood #Natural Language Processing Techniques #Natural language processing #Pattern recognition (psychology) #Quality (philosophy) #Sequence (biology) #Speech Recognition and Synthesis #Speech recognition #Statistics #Topic Modeling #Translation (biology) #cs.CL
13. Bayesian Model Averaging of Chain Event Graphs for Robust Explanatory Modelling
    2022/02/24 by Peter Strong, Strong, Peter, Jim Q. Smith +1 · 1 citation
    Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Artificial intelligence #Bayesian Modeling and Causal Inference #Bayesian inference #Bayesian probability #Bioinformatics and Genomic Networks #Class (philosophy) #Computer science #Context (archaeology) #Data mining #Event (particle physics) #FOS: Computer and information sciences #Geography #Graphical model #Independence (probability theory) #Inference #Machine learning #Mathematics #Maximum a posteriori estimation #Maximum likelihood #Metabolomics and Mass Spectrometry Studies #Methodology (stat.ME) #Model selection #Probabilistic logic #Selection (genetic algorithm) #Statistics
14. Model-based Clustering with Missing Not At Random Data
    2021/12/20 by Aude Sportisse, Sportisse, Aude, Matthieu Marbac +11 · 1 citation
    Computer Science · Mathematics · #Artificial intelligence #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #Categorical variable #Class (philosophy) #Cluster analysis #Computer science #Data mining #Expectation–maximization algorithm #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine learning #Mathematics #Maximum likelihood #Missing data #Pattern recognition (psychology) #Reinterpretation #Statistics
15. Power Generalized DUS Transformation of Exponential Distribution
    2021/11/17 by Beenu Thomas, Thomas, Beenu, Chacko V M +2 · 1 citation
    Decision Sciences · Engineering · Mathematics · #Applied mathematics #Computer science #Data mining #Data transformation #Distribution (mathematics) #Exponential distribution #Exponential family #Exponential function #Exponentiation #FOS: Computer and information sciences #Gamma distribution #Mathematical analysis #Mathematics #Maximum likelihood #Methodology (stat.ME) #Probabilistic and Robust Engineering Design #Reliability and Maintenance Optimization #Statistical Distribution Estimation and Applications #Statistics #Transformation (genetics) #stat.ME
16. Estimation of time-specific intervention effects on continuously distributed time-to-event outcomes by targeted maximum likelihood estimation
    2021/06/21 by Helene C. W. Rytgaard, Helene Charlotte Wiese Rytgaard, Rytgaard, Helene Charlotte Wiese +4 · 3 citations
    Economics, Econometrics and Finance · Engineering · Mathematics · #Advanced Causal Inference Techniques #Computer science #Econometrics #Engineering #Estimation #Estimation theory #Estimator #FOS: Computer and information sciences #Health Systems, Economic Evaluations, Quality of Life #Lasso (programming language) #Mathematics #Maximum likelihood #Methodology (stat.ME) #Poisson distribution #Statistical Methods and Bayesian Inference #Statistics #stat.ME
17. RCoNet: Deformable Mutual Information Maximization and High-order Uncertainty-aware Learning for Robust COVID-19 Detection
    2021/02/22 by Shunjie Dong, Dong, Shunjie, Qianqian Yang +7 · 1 citation
    Computer Science · Engineering · Mathematics · Medicine · #Anomaly Detection Techniques and Applications #Artificial intelligence #Big data #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #Computer science #Coronavirus disease 2019 (COVID-19) #Data mining #Discriminative model #Expectation–maximization algorithm #FOS: Computer and information sciences #FOS: Electrical engineering #Feature (linguistics) #Image (mathematics) #Image and Video Processing (eess.IV) #Machine learning #Mathematical optimization #Mathematics #Maximization #Maximum likelihood #Medical diagnosis #Medical imaging #Medicine #Mutual information #Noise (video) #Pattern recognition (psychology) #Radiology #Radiomics and Machine Learning in Medical Imaging #Robust optimization #Statistics #cs.CV #eess.IV #electronic engineering #information engineering
18. Numerical Issues in Maximum Likelihood Parameter Estimation for Gaussian Process Interpolation
    2021/01/24 by Subhasish Basak, Sébastien Petit, Julien Bect +2 · 1 voice · 1 citation
    Computer Science · Decision Sciences · Mathematics · #Advanced Multi-Objective Optimization Algorithms #Algorithm #Artificial intelligence #Bayesian optimization #Bayesian probability #Computer science #Estimation theory #Gaussian #Gaussian Processes and Bayesian Inference #Gaussian process #Implementation #Interpolation (computer graphics) #Machine learning #Mathematical optimization #Mathematics #Maximum likelihood #Process (computing) #Programming language #Simulation Techniques and Applications #Software engineering #Statistics
19. The Tupí-Guaraní language family
    2020/11/12 by Fabrício Ferraz Gerardi, Stanislav Reichert · 2 citations
    Arts and Humanities · Environmental Science · Mathematics · Social Sciences · #Amazonian Archaeology and Ethnohistory #Artificial intelligence #Bayesian probability #Biology #Computer science #Econometrics #Economics #Estimation #Fish biology, ecology, and behavior #Genealogy #Genetics #Geography #History #Language and cultural evolution #Linguistics #Mathematics #Maximum likelihood #Philosophy #Phylogenetic tree #Statistics
20. Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent
    2020/11/02 by Frederik Künstner, Frederik Kunstner, Kunstner, Frederik +4 · 4 citations
    Computer Science · Mathematics · #Applied mathematics #Artificial intelligence #Artificial neural network #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #Bregman divergence #Computer science #Convergence (economics) #Divergence (linguistics) #Expectation–maximization algorithm #Exponential family #Exponential function #FOS: Computer and information sciences #Gaussian #Gaussian Processes and Bayesian Inference #Gradient descent #Invariant (physics) #Kullback–Leibler divergence #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mathematical analysis #Mathematical optimization #Mathematics #Maximum likelihood #Parametrization (atmospheric modeling) #Physics #Probabilistic logic #Statistical Methods and Inference #Statistics #cs.LG #stat.ML
21. Greater Than the Sum of its Parts: Computationally Flexible Bayesian Hierarchical Modeling
    2020/10/23 by Devin S. Johnson, Johnson, Devin S., Brian M. Brost +3 · 1 citation
    Environmental Science · Mathematics · #Algorithm #Bayesian inference #Bayesian probability #Computation (stat.CO) #Computer science #Data mining #Ecology and Vegetation Dynamics Studies #Estimator #FOS: Computer and information sciences #Hierarchical database model #Mathematics #Maximum a posteriori estimation #Maximum likelihood #Methodology (stat.ME) #Population #Posterior probability #Random effects model #Soil Geostatistics and Mapping #Statistical Methods and Bayesian Inference #Statistics #stat.CO #stat.ME
22. Maximum likelihood estimation for discrete exponential families and random graphs
    2019/11/29 by Krzysztof Bogdan, Bogdan, Krzysztof, Michał Bosy +3 · 1 citation
    Computer Science · Decision Sciences · Mathematics · #05C80 #62H12 #Applied mathematics #Bayesian Methods and Mixture Models #Combinatorics #Combinatorics (math.CO) #Estimator #Exponential distribution #Exponential family #Exponential function #Exponential random graph models #FOS: Mathematics #Graph #Independent and identically distributed random variables #Mathematical analysis #Mathematics #Maximum likelihood #Maximum likelihood sequence estimation #Probability (math.PR) #Probability and Risk Models #Random graph #Random variable #Simple (philosophy) #Statistical Methods and Inference #Statistics #Statistics Theory (math.ST) #math.CO #math.PR #math.ST #msc:05C80 #msc:62H12 #stat.TH
23. On the overestimation of widely applicable Bayesian information criterion
    2019/08/28 by Toru Imai, Imai, Toru · 1 citation
    Computer Science · Mathematics · #Applied mathematics #Artificial intelligence #Bayesian Methods and Mixture Models #Bayesian information criterion #Bayesian probability #Computer science #Econometrics #Estimator #FOS: Computer and information sciences #FOS: Mathematics #Information Criteria #Machine Learning (stat.ML) #Marginal likelihood #Mathematics #Maximum likelihood #Methodology (stat.ME) #Model selection #Physics #Selection (genetic algorithm) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics #Statistics Theory (math.ST) #Term (time) #math.ST #stat.ME #stat.ML #stat.TH
24. Copula information criterion for model selection with two-stage maximum likelihood estimation
    2019/02/10 by Vinnie Ko, Nils Lid Hjort · 1 citation
    Economics, Econometrics and Finance · Mathematics · #Artificial intelligence #Computer science #Copula (linguistics) #Covariate #Econometrics #Financial Risk and Volatility Modeling #Inference #Information Criteria #Mathematics #Maximum likelihood #Model selection #Parametric model #Parametric statistics #Statistical Distribution Estimation and Applications #Statistical Methods and Inference #Statistics
25. 19 dubious ways to compute the marginal likelihood of a phylogenetic\n tree topology
    2018/11/28 by Mathieu Fourment, Fourment, Mathieu, Andrew F. Magee +10 · 4 citations
    Biochemistry, Genetics and Molecular Biology · Earth and Planetary Sciences · Mathematics · #Algorithm #Benchmark (surveying) #Computation (stat.CO) #Computer science #Dimension (graph theory) #Estimator #Evolution and Paleontology Studies #FOS: Biological sciences #FOS: Computer and information sciences #Genomics and Phylogenetic Studies #Marginal likelihood #Mathematical optimization #Mathematics #Maximum likelihood #Morphological variations and asymmetry #Network topology #Populations and Evolution (q-bio.PE) #Statistics #Tree (set theory) #q-bio.PE #stat.CO
26. Nonparametric independence screening for ultra-high dimensional generalized varying coefficient models with longitudinal data
    2018/11/13 by Shen Zhang, Peixin Zhao, Gaorong Li +1 · 1 citation
    Computer Science · Economics, Econometrics and Finance · Mathematics · #Applied mathematics #Bayesian Methods and Mixture Models #Computer science #Correlation coefficient #Covariate #Estimating equations #Extension (predicate logic) #Financial Risk and Volatility Modeling #Gee #Generalized estimating equation #Generalized linear model #Independence (probability theory) #Marginal model #Mathematical optimization #Mathematics #Maximum likelihood #Nonparametric statistics #Regression analysis #Statistical Methods and Inference #Statistics
27. Model-Based Measures for Detecting and Quantifying Response Bias
    2018/06/15 by R. Philip Chalmers · 10 citations
    Computer Science · Decision Sciences · Mathematics · #Advanced Causal Inference Techniques #Advanced Statistical Modeling Techniques #Categorical variable #Computer science #Differential item functioning #Econometrics #Item response theory #Marginal likelihood #Mathematics #Maximum likelihood #Monte Carlo method #Psychometric Methodologies and Testing #Psychometrics #Response bias #Sample size determination #Statistical hypothesis testing #Statistics
28. Lecture Notes: Temporal Point Processes and the Conditional Intensity Function
    2018/06/01 by Jakob Gulddahl Rasmussen, Rasmussen, Jakob Gulddahl · 1 voice · 12 citations
    Biochemistry, Genetics and Molecular Biology · Mathematics · #Algorithm #Artificial intelligence #Computer science #Diffusion and Search Dynamics #Econometrics #Focus (optics) #Function (biology) #Inference #Intensity (physics) #Likelihood function #Mathematics #Maximum likelihood #Optics #Physics #Point (geometry) #Point process #Point processes and geometric inequalities #Residual #Statistics #stat.ME
29. Bayesian model selection for the latent position cluster model for Social Networks
    2017/02/01 by Caitríona M. Ryan, Caitriona Ryan, Ryan, Caitriona +4 · 3 citations
    Computer Science · Mathematics · #Artificial intelligence #Bayesian Methods and Mixture Models #Bayesian inference #Bayesian linear regression #Bayesian probability #Computation (stat.CO) #Computer science #Conjugate prior #Expectation–maximization algorithm #FOS: Computer and information sciences #Inference #Latent class model #Latent variable #Latent variable model #Machine learning #Markov chain Monte Carlo #Mathematics #Maximum likelihood #Mixture model #Model selection #Position (finance) #Posterior predictive distribution #Posterior probability #Reversible-jump Markov chain Monte Carlo #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistical model #Statistics #stat.CO
30. Full Information Maximum Likelihood Estimation for Latent Variable Interactions With Incomplete Indicators
    2016/11/11 by Heining Cham, Evgeniya Reshetnyak, Barry Rosenfeld +1 · 30 citations
    Computer Science · Mathematics · Psychology · #Advanced Statistical Modeling Techniques #Computer science #Econometrics #Interaction #Latent variable #Latent variable model #Mathematics #Maximum likelihood #Mental Health Research Topics #Missing data #Regression #Regression analysis #Statistical Methods and Inference #Statistics #Structural equation modeling

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