Mark Girolami - RankMe

76 papers A* 2A 4B 1Misc 1Journal 65Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Hierarchical Inference and Closure Learning via Adaptive Surrogates for ODEs and PDEs. CoRR Pengyu Zhang, Arnaud Vadeboncoeur, Alex Glyn-Davies, Mark Girolami
2026	J	`jnl`	Improving Embedding of Graphs With Missing Data by Soft Manifolds. IEEE Trans. Pattern Anal. Mach. Intell. Andrea Marinoni, Pietro Liò, Alessandro Barp, Mark Girolami
2026	J	`jnl`	Koopman Autoencoders with Continuous-Time Latent Dynamics for Fluid Dynamics Forecasting. CoRR Rares Grozavescu, Pengyu Zhang, Etienne Meunier, Mark Girolami
2026	J	`jnl`	Towards Efficient and Stable Ocean State Forecasting: A Continuous-Time Koopman Approach. CoRR Rares Grozavescu, Pengyu Zhang, Mark Girolami, Etienne Meunier
2025	J	`jnl`	Autoencoders in Function Space. J. Mach. Learn. Res. Justin Bunker, Mark Girolami, Hefin Lambley, Andrew M. Stuart, Timothy John Sullivan
2025	J	`jnl`	Collaborative prognosis using a Weibull statistical hierarchical model. Reliab. Eng. Syst. Saf. Maharshi Harshadbhai Dhada, Lawrence A. Bull, Mark Girolami, Ajith Kumar Parlikad
2025	J	`jnl`	Efficient Deconvolution in Populational Inverse Problems. CoRR Arnaud Vadeboncoeur, Mark Girolami, Andrew M. Stuart
2025	J	`jnl`	Efficient Prior Calibration from Indirect Data. SIAM J. Sci. Comput. Ömer Deniz Akyildiz, Mark Girolami, Andrew M. Stuart, Arnaud Vadeboncoeur
2025	J	`jnl`	Error analysis for a statistical finite element method. J. Multivar. Anal. Toni Karvonen, Fehmi Cirak, Mark Girolami
2025	J	`jnl`	Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later. CoRR Arnaud Vadeboncoeur, Gregory Duthé, Mark Girolami, Eleni N. Chatzi
2025	J	`jnl`	Physics-informed machine learning digital twin for reconstructing prostate cancer tumor growth via PSA tests. npj Digit. Medicine Daniel Camacho-Gómez, Carlos Borau, José Manuel García-Aznar, María José Gómez-Benito, Mark Girolami, María Ángeles Pérez
2025	J	`jnl`	Probabilistic Super-Resolution for High-Fidelity Physical System Simulations with Uncertainty Quantification. CoRR Pengyu Zhang, Connor Duffin, Alex Glyn-Davies, Arnaud Vadeboncoeur, Mark Girolami
2025	J	`jnl`	Retrieval-augmented reasoning with lean language models. CoRR Ryan Sze-Yin Chan, Federico Nanni, Tomas Lazauskas, Rosie Wood, Penelope Yong, Lionel Tarassenko, Mark Girolami, James Geddes, Andrew B. Duncan
2025	J	`jnl`	Statistical Finite Elements via Interacting Particle Langevin Dynamics. SIAM/ASA J. Uncertain. Quantification Alex Glyn-Davies, Connor Duffin, Ieva Kazlauskaite, Mark Girolami, Ömer Deniz Akyildiz
2024	J	`jnl`	A Primer on Variational Inference for Physics-Informed Deep Generative Modelling. CoRR Alex Glyn-Davies, Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami
2024	J	`jnl`	Autoencoders in Function Space. CoRR Justin Bunker, Mark Girolami, Hefin Lambley, Andrew M. Stuart, Tim Sullivan
2024	J	`jnl`	Bayesian dynamic modelling for probabilistic prediction of pavement condition. Eng. Appl. Artif. Intell. Yiming Zhang, Alix Marie d'Avigneau, Georgios M. Hadjidemetriou, Lavindra de Silva, Mark Girolami, Ioannis K. Brilakis
2024	J	`jnl`	Efficient Prior Calibration From Indirect Data. CoRR Ömer Deniz Akyildiz, Mark Girolami, Andrew M. Stuart, Arnaud Vadeboncoeur
2024	A*	`conf`	Generating Origin-Destination Matrices in Neural Spatial Interaction Models. NeurIPS Ioannis Zachos, Mark Girolami, Theodoros Damoulas
2024	J	`jnl`	Generating Origin-Destination Matrices in Neural Spatial Interaction Models. CoRR Ioannis Zachos, Mark Girolami, Theodoros Damoulas
2024	J	`jnl`	Generative broad Bayesian (GBB) imputer for missing data imputation with uncertainty quantification. Knowl. Based Syst. Sin-Chi Kuok, Ka-Veng Yuen, Tim J. Dodwell, Mark Girolami
2024	J	`jnl`	Near Real-Time Social Distance Estimation In London. Comput. J. James Walsh, Oluwafunmilola Kesa, Andrew Wang, Mihai Ilas, Patrick O'Hara, Oscar Giles, Neil Dhir, Mark Girolami, Theodoros Damoulas
2024	A	`conf`	Riemannian Laplace Approximation with the Fisher Metric. AISTATS Hanlin Yu, Marcelo Hartmann, Bernardo Williams Moreno Sanchez, Mark Girolami, Arto Klami
2024	J	`jnl`	Targeted Separation and Convergence with Kernel Discrepancies. J. Mach. Learn. Res. Alessandro Barp, Carl-Johann Simon-Gabriel, Mark Girolami, Lester Mackey
2024	J	`jnl`	The Bayesian Approach to Inverse Robin Problems. SIAM/ASA J. Uncertain. Quantification Aksel K. Rasmussen, Fanny Seizilles, Mark Girolami, Ieva Kazlauskaite
2024	J	`jnl`	Tweedie Moment Projected Diffusions for Inverse Problems. Trans. Mach. Learn. Res. Benjamin Boys, Mark Girolami, Jakiw Pidstrigach, Sebastian Reich, Alan Mosca, Ömer Deniz Akyildiz
2024	J	`jnl`	Φ-DVAE: Physics-informed dynamical variational autoencoders for unstructured data assimilation. J. Comput. Phys. Alex Glyn-Davies, Connor Duffin, Ömer Deniz Akyildiz, Mark Girolami
2023	J	`jnl`	Bayesian learning via neural Schrödinger-Föllmer flows. Stat. Comput. Francisco Vargas, Andrius Ovsianas, David Fernandes, Mark Girolami, Neil D. Lawrence, Nikolas Nüsken
2023	J	`jnl`	Encoding Domain Expertise into Multilevel Models for Source Location. CoRR Lawrence A. Bull, Matthew R. Jones, Elizabeth J. Cross, Andrew B. Duncan, Mark Girolami
2023	J	`jnl`	Fully probabilistic deep models for forward and inverse problems in parametric PDEs. J. Comput. Phys. Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak
2023	J	`jnl`	Hierarchical Bayesian modeling for knowledge transfer across engineering fleets via multitask learning. Comput. Aided Civ. Infrastructure Eng. Lawrence A. Bull, Domenic Di Francesco, Maharshi Harshadbhai Dhada, Olof Steinert, Tony Lindgren, Ajith Kumar Parlikad, Andrew B. Duncan, Mark Girolami
2023	J	`jnl`	Improving embedding of graphs with missing data by soft manifolds. CoRR Andrea Marinoni, Pietro Lio', Alessandro Barp, Christian Jutten, Mark Girolami
2023	Misc	`conf`	Incorporating Reliability in Graph Information Propagation by Fluid Dynamics Diffusion: A case of Multimodal Semisupervised Deep Learning. ICASSP Andrea Marinoni, Marine Mercier, Qian Shi, Sivasakthy Selvakumaran, Mark Girolami
2023	J	`jnl`	Inferring networks from time series: a neural approach. CoRR Thomas Gaskin, Grigorios A. Pavliotis, Mark Girolami
2023	A*	`conf`	Random Grid Neural Processes for Parametric Partial Differential Equations. ICML Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz
2023	J	`jnl`	Random Grid Neural Processes for Parametric Partial Differential Equations. CoRR Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz
2023	J	`jnl`	Riemannian Laplace Approximation with the Fisher Metric. CoRR Hanlin Yu, Marcelo Hartmann, Bernardo Williams, Mark Girolami, Arto Klami
2023	J	`jnl`	Sobolev Spaces, Kernels and Discrepancies over Hyperspheres. Trans. Mach. Learn. Res. Simon Hubbert, Emilio Porcu, Chris J. Oates, Mark Girolami
2023	J	`jnl`	Theoretical Guarantees for the Statistical Finite Element Method. SIAM/ASA J. Uncertain. Quantification Yanni Papandreou, Jon Cockayne, Mark Girolami, Andrew B. Duncan
2023	J	`jnl`	Warped geometric information on the optimisation of Euclidean functions. CoRR Marcelo Hartmann, Bernardo Williams, Hanlin Yu, Mark Girolami, Alessandro Barp, Arto Klami
2022	J	`jnl`	$Φ$-DVAE: Learning Physically Interpretable Representations with Nonlinear Filtering. CoRR Alex Glyn-Davies, Connor Duffin, Ömer Deniz Akyildiz, Mark Girolami
2022	J	`jnl`	A mixture modeling approach for clustering log files with coreset and user feedback. Pattern Recognit. Lett. Justin Bunker, Kristal Curtis, Mark Girolami, Ram Sriharsha
2022	J	`jnl`	Anomaly detection in streaming data with gaussian process based stochastic differential equations. Pattern Recognit. Lett. Alex Glyn-Davies, Mark Girolami
2022	J	`jnl`	Deep Probabilistic Models for Forward and Inverse Problems in Parametric PDEs. CoRR Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak
2022	J	`jnl`	Error analysis for a statistical finite element method. CoRR Toni Karvonen, Fehmi Cirak, Mark Girolami
2022	J	`jnl`	Knowledge Transfer in Engineering Fleets: Hierarchical Bayesian Modelling for Multi-Task Learning. CoRR Lawrence A. Bull, Maharshi Harshadbhai Dhada, Olof Steinert, Tony Lindgren, Ajith Kumar Parlikad, Andrew B. Duncan, Mark Girolami
2022	J	`jnl`	Lagrangian Manifold Monte Carlo on Monge Patches. CoRR Marcelo Hartmann, Mark Girolami, Arto Klami
2022	A	`conf`	Lagrangian manifold Monte Carlo on Monge patches. AISTATS Marcelo Hartmann, Mark Girolami, Arto Klami
2022	J	`jnl`	Low-rank statistical finite elements for scalable model-data synthesis. J. Comput. Phys. Connor Duffin, Edward Cripps, Thomas Stemler, Mark Girolami
2022	J	`jnl`	Neural parameter calibration for large-scale multi-agent models. CoRR Thomas Gaskin, Grigorios A. Pavliotis, Mark Girolami
2022	J	`jnl`	Sobolev Spaces, Kernels and Discrepancies over Hyperspheres. CoRR Simon Hubbert, Emilio Porcu, Chris J. Oates, Mark Girolami
2022	J	`jnl`	Statistical Finite Elements via Langevin Dynamics. SIAM/ASA J. Uncertain. Quantification Ömer Deniz Akyildiz, Connor Duffin, Sotirios Sabanis, Mark Girolami
2022	J	`jnl`	Targeted Separation and Convergence with Kernel Discrepancies. CoRR Alessandro Barp, Carl-Johann Simon-Gabriel, Mark Girolami, Lester Mackey
2021	J	`jnl`	A Self-Sensing Digital Twin of a Railway Bridge using the Statistical Finite Element Method. CoRR Eky Febrianto, Liam J. Butler, Mark Girolami, Fehmi Cirak
2021	J	`jnl`	A graph representation based on fluid diffusion model for multimodal data analysis: theoretical aspects and enhanced community detection. CoRR Andrea Marinoni, Christian Jutten, Mark Girolami
2021	J	`jnl`	Bayesian Learning via Neural Schrödinger-Föllmer Flows. CoRR Francisco Vargas, Andrius Ovsianas, David Fernandes, Mark Girolami, Neil D. Lawrence, Nikolas Nüsken
2021	J	`jnl`	Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness. J. Mach. Learn. Res. George Wynne, François-Xavier Briol, Mark Girolami
2021	J	`jnl`	Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction. CoRR Andrea Marinoni, Saloua Chlaily, Eduard Khachatrian, Torbjørn Eltoft, Sivasakthy Selvakumaran, Mark Girolami, Christian Jutten
2021	J	`jnl`	Integration in reproducing kernel Hilbert spaces of Gaussian kernels. Math. Comput. Toni Karvonen, Chris J. Oates, Mark Girolami
2021	J	`jnl`	Low-rank statistical finite elements for scalable model-data synthesis. CoRR Connor Duffin, Edward Cripps, Thomas Stemler, Mark Girolami
2021	J	`jnl`	PeriPy - A High Performance OpenCL Peridynamics Package. CoRR Benjamin Boys, Tim J. Dodwell, Mark Hobbs, Mark Girolami
2021	J	`jnl`	Scaling digital twins from the artisanal to the industrial. Nat. Comput. Sci. Steven A. Niederer, Michael S. Sacks, Mark Girolami, Karen Willcox
2021	J	`jnl`	Statistical Finite Elements via Langevin Dynamics. CoRR Ömer Deniz Akyildiz, Connor Duffin, Sotirios Sabanis, Mark Girolami
2021	J	`jnl`	Theoretical Guarantees for the Statistical Finite Element Method. CoRR Yanni Papandreou, Jon Cockayne, Mark Girolami, Andrew B. Duncan
2021	J	`jnl`	Uncertainty quantification for data-driven turbulence modelling with Mondrian forests. J. Comput. Phys. Ashley Scillitoe, Pranay Seshadri, Mark Girolami
2020	J	`jnl`	Bayesian Assessments of Aeroengine Performance. CoRR Pranay Seshadri, Andrew B. Duncan, George Thorne, Geoffrey T. Parks, Mark Girolami
2020	J	`jnl`	Continuous calibration of a digital twin: comparison of particle filter and Bayesian calibration approaches. CoRR Rebecca Ward, Ruchi Choudhary, Alastair Gregory, Mark Girolami
2020	A	`conf`	Dynamic content based ranking. AISTATS Seppo Virtanen, Mark Girolami
2020	J	`jnl`	Integration in reproducing kernel Hilbert spaces of Gaussian kernels. CoRR Toni Karvonen, Chris J. Oates, Mark Girolami
2020	J	`jnl`	Posterior inference for sparse hierarchical non-stationary models. Comput. Stat. Data Anal. Karla Monterrubio-Gómez, Lassi Roininen, Sara Wade, Theodoros Damoulas, Mark Girolami
2019	J	`jnl`	A Methodology for Prognostics Under the Conditions of Limited Failure Data Availability. IEEE Access Gishan Don Ranasinghe, Tony Lindgren, Mark Girolami, Ajith Kumar Parlikad
2010	—	`ch.`	System Identification and Model Ranking: The Bayesian Perspective. Learning and Inference in Computational Systems Biology Mark Girolami, Ben Calderhead, Vladislav Vyshemirsky
2004	B	`conf`	Topic based language models for ad hoc information retrieval. IJCNN Leif Azzopardi, Mark Girolami, C. J. van Rijsbergen
1997	—	`conf`	Fahlman-Type Activation Functions Applied to Nonlinear PCA Networks Provide a Generalised Independent Component Analysis. ICANNGA Mark Girolami, Colin Fyfe
1997	A	`conf`	Multivariate Density Factorization for Independent Component Analysis: An Unsupervised Artificial Neural Network Approach. AISTATS Mark Girolami, Colin Fyfe
1997	—	`conf`	Principal Components Identify MLP Hidden Layer Size for Optimal Generalisation Performance. ICANNGA Mark Girolami