vix.ing · top · new · best · stats · spec

Girolami, Mark

  1. Hamiltonian Monte Carlo for Hierarchical Models
    2013/12/03 by M. Betancourt, Mark Girolami, Betancourt, M. J. +1 · 14 citations
    Mathematics · Computer Science · #Markov Chains and Monte Carlo Methods #Bayesian Methods and Mixture Models
  2. Control functionals for Monte Carlo integration
    2014/10/09 by Chris J. Oates, Oates, Chris J., Mark Girolami +3 · 9 citations
    Computer Science · Mathematics · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Markov Chains and Monte Carlo Methods #Methodology (stat.ME) #Statistical Methods and Inference
  3. Tweedie Moment Projected Diffusions For Inverse Problems
    2023/10/10 by Benjamin Boys, Boys, Benjamin, Mark Girolami +9 · 14 citations
    Computer Science · Medicine · #Advanced Neuroimaging Techniques and Applications #Computation (stat.CO) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis
  4. On the Geometric Ergodicity of Hamiltonian Monte Carlo
    2016/01/29 by Livingstone, Samuel, Betancourt, Michael, Byrne, Simon +1 · 5 citations
    #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (stat.ML) #Methodology (stat.ME)
  5. Convergence Guarantees for Gaussian Process Means With Misspecified\n Likelihoods and Smoothness
    2020/01/29 by George Wynne, Wynne, George, François‐Xavier Briol +3 · 6 citations
    Computer Science · Decision Sciences · Mathematics · #Advanced Bandit Algorithms Research #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA) #Statistical Methods and Inference #Statistics Theory (math.ST)
  6. Statistical Inference for Generative Models with Maximum Mean Discrepancy
    2019/06/13 by François‐Xavier Briol, Briol, Francois-Xavier, Alessandro Barp +5 · 7 citations
    Mathematics · Computer Science · #Markov Chains and Monte Carlo Methods #Gaussian Processes and Bayesian Inference #Bayesian Methods and Mixture Models
  7. Bayesian Learning via Neural Schrödinger-Föllmer Flows
    2021/11/20 by Francisco Vargas, Andrius Ovsianas, Vargas, Francisco +9 · 5 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications
  8. The Geometric Foundations of Hamiltonian Monte Carlo
    2014/10/19 by Betancourt, M. J., Byrne, Simon, Livingstone, Samuel +1 · 3 citations
    #FOS: Computer and information sciences #Methodology (stat.ME)
  9. A Riemann-Stein Kernel Method
    2018/10/11 by Alessandro Barp, Barp, Alessandro, Chris J. Oates +5 · 3 citations
    Engineering · Mathematics · #Advanced Numerical Analysis Techniques #FOS: Mathematics #Mathematical functions and polynomials #Numerical methods in inverse problems #Statistics Theory (math.ST)
  10. Minimum Stein Discrepancy Estimators
    2019/06/19 by Barp, Alessandro, Briol, Francois-Xavier, Duncan, Andrew B. +2 · 3 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistics Theory (math.ST)
  11. Convergence Rates for a Class of Estimators Based on Stein's Method
    2016/03/10 by Oates, Chris J., Cockayne, Jon, Briol, François-Xavier +1 · 2 citations
    #FOS: Mathematics #Statistics Theory (math.ST)
  12. Hyperpriors for Matérn fields with applications in Bayesian inversion
    2016/12/09 by Roininen, Lassi, Girolami, Mark, Lasanen, Sari +1 · 2 citations
    #FOS: Mathematics #Statistics Theory (math.ST)
  13. Probabilistic Integration: A Role in Statistical Computation?
    2015/12/03 by Briol, François-Xavier, Oates, Chris. J., Girolami, Mark +2 · 2 citations
    #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Numerical Analysis (math.NA) #Statistics Theory (math.ST)
  14. Targeted Separation and Convergence with Kernel Discrepancies
    2022/09/26 by Alessandro Barp, Carl-Johann Simon-Gabriel, Barp, Alessandro +5 · 3 citations
    Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Statistical Methods and Inference #Statistics Theory (math.ST)
  15. Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
    2023/03/23 by Akyildiz, Ö. Deniz, Crucinio, Francesca Romana, Girolami, Mark +2 · 3 citations
    #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Probability (math.PR)
  16. Semi-Exact Control Functionals From Sard's Method
    2020/01/31 by South, Leah F., Karvonen, Toni, Nemeth, Chris +2 · 2 citations
    #Computation (stat.CO) #FOS: Computer and information sciences #Methodology (stat.ME)
  17. Probabilistic Models for Integration Error in the Assessment of\n Functional Cardiac Models
    2016/06/22 by Chris J. Oates, Oates, Chris. J., Steven Niederer +7 · 2 citations
    Computer Science · Decision Sciences · Mathematics · Medicine · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Hemodynamic Monitoring and Therapy #Methodology (stat.ME) #Probabilistic and Robust Engineering Design #Statistical Methods and Inference
  18. Bayesian Quadrature for Multiple Related Integrals
    2018/01/12 by Xiaoyue Xi, François‐Xavier Briol, Xi, Xiaoyue +3 · 2 citations
    Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Numerical Analysis (math.NA) #Probabilistic and Robust Engineering Design
  19. Probabilistic Model Checking of DTMC Models of User Activity Patterns
    2014/03/20 by Oana Andrei, Muffy Calder, Andrei, Oana +5 · 1 citation
    Business, Management and Accounting · Computer Science · #Advanced Software Engineering Methodologies #Business Process Modeling and Analysis #FOS: Computer and information sciences #Logic in Computer Science (cs.LO) #Software Engineering (cs.SE) #Software System Performance and Reliability
  20. Optimizing The Integrator Step Size for Hamiltonian Monte Carlo
    2014/11/24 by Betancourt, M. J., Byrne, Simon, Girolami, Mark · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Methodology (stat.ME) #Statistics Theory (math.ST)
  21. Probability Measures for Numerical Solutions of Differential Equations
    2015/06/15 by Conrad, Patrick R., Girolami, Mark, Särkkä, Simo +2 · 1 citation
    #FOS: Computer and information sciences #Methodology (stat.ME)
  22. Autoencoders in Function Space
    2024/08/02 by Justin Bunker, Bunker, Justin, Mark Girolami +7 · 3 citations
    Computer Science · #Neural Networks and Applications
  23. Multi-resolution Multi-task Gaussian Processes
    2019/06/19 by Oliver Hamelijnck, Hamelijnck, Oliver, Theodoros Damoulas +5 · 1 citation
    Computer Science · Environmental Science · #Air Quality Monitoring and Forecasting #Atmospheric and Environmental Gas Dynamics #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  24. Efficient Prior Calibration From Indirect Data
    2024/05/28 by Akyildiz, O. Deniz, Girolami, Mark, Stuart, Andrew M. +1 · 3 citations
    #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  25. Φ-DVAE: Physics-Informed Dynamical Variational Autoencoders for Unstructured Data Assimilation
    2022/09/30 by Alex Glyn-Davies, Connor Duffin, Glyn-Davies, Alex +5 · 1 voice · 1 citation
    Physics and Astronomy · Computer Science · Earth and Planetary Sciences · #stat.ML #cs.LG #physics.comp-ph #stat.CO
  26. Inferring networks from time series: a neural approach
    2023/03/30 by Gaskin, Thomas, Pavliotis, Grigorios A., Girolami, Mark · 2 citations
    #37A50 #49M41 #65K05 #68T07 #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #G.3 #I.2.8 #J.2 #Machine Learning (cs.LG) #Optimization and Control (math.OC)
  27. Statistical Finite Elements via Langevin Dynamics
    2021/10/21 by Ömer Deniz Akyıldız, Connor Duffin, Akyildiz, Ömer Deniz +5 · 1 citation
    Decision Sciences · Mathematics · Physics and Astronomy · #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Probabilistic and Robust Engineering Design
  28. Model selection and sensitivity analysis in the biomechanics of soft tissues: a case study on the human knee meniscus
    2021/12/26 by Elmukashfi, Elsiddig, Marchiori, Gregorio, Berni, Matteo +5 · 1 citation
    #Biological Physics (physics.bio-ph) #FOS: Physical sciences #Medical Physics (physics.med-ph)
  29. Lagrangian Manifold Monte Carlo on Monge Patches
    2022/02/01 by Marcelo Hartmann, Hartmann, Marcelo, Mark Girolami +3 · 1 citation
    Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Markov Chains and Monte Carlo Methods #Methodology (stat.ME) #Topological and Geometric Data Analysis
  30. Sobolev Spaces, Kernels and Discrepancies over Hyperspheres
    2022/11/16 by Simon Hubbert, Hubbert, Simon, Emilio Porcu +5 · 1 citation
    Engineering · Mathematics · Medicine · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Medical Imaging Techniques and Applications #Numerical methods in engineering #Numerical methods in inverse problems
  31. Integration in reproducing kernel Hilbert spaces of Gaussian kernels
    2020/04/27 by Karvonen, Toni, Oates, Chris J., Girolami, Mark · 1 citation
    #FOS: Mathematics #Functional Analysis (math.FA) #Numerical Analysis (math.NA)
  32. Error analysis for a statistical finite element method
    2022/01/19 by Karvonen, Toni, Cirak, Fehmi, Girolami, Mark · 1 citation
    #FOS: Mathematics #Numerical Analysis (math.NA) #Statistics Theory (math.ST)
  33. The Bayesian approach to inverse Robin problems
    2023/11/29 by Rasmussen, Aksel Kaastrup, Seizilles, Fanny, Girolami, Mark +1 · 1 citation
    #35R30 #62F15 #62G20 #Analysis of PDEs (math.AP) #FOS: Mathematics #Statistics Theory (math.ST)
  34. Efficient Deconvolution in Populational Inverse Problems
    2025/05/26 by Vadeboncoeur, Arnaud, Girolami, Mark, Stuart, Andrew M. · 3 citations
    #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  35. Statistical Finite Elements via Interacting Particle Langevin Dynamics
    2024/09/11 by Alex Glyn-Davies, Glyn-Davies, Alex, Connor Duffin +7 · 1 citation
    Computer Science · Engineering · Physics and Astronomy · #Computation (stat.CO) #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Nanopore and Nanochannel Transport Studies #Stochastic Gradient Optimization Techniques #Theoretical and Computational Physics
  36. Generating Origin-Destination Matrices in Neural Spatial Interaction Models
    2024/10/09 by Ioannis Zachos, Mark Girolami, Zachos, Ioannis +3 · 1 citation
    Computer Science · Engineering · #Advanced Image and Video Retrieval Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Spatial Cognition and Navigation