Semantic Information Pursuit for Multimodal Data Analysis
Lead Research Organisation:
University of Oxford
Department Name: Statistics
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
People |
ORCID iD |
Arnaud Doucet (Principal Investigator) |
Publications
Campbell A
(2021)
Online Variational Filtering and Parameter Learning
Mikhailiuk A
(2020)
Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality
Hellström F
(2023)
Comparing Comparators in Generalization Bounds
Alquier P
(2020)
Estimation of copulas via Maximum Mean Discrepancy
Clerico E
(2022)
Chained Generalisation Bounds
Campbell A
(2023)
Trans-Dimensional Generative Modeling via Jump Diffusion Models
Bulathwela S
(2020)
SUM'20: State-based User Modelling
Phillips A
(2022)
Spectral Diffusion Processes
Benton J
(2022)
From Denoising Diffusions to Denoising Markov Models
Xu T
(2019)
An Accelerated Correlation Filter Tracker
Campbell A
(2022)
A Continuous Time Framework for Discrete Denoising Models
Viallard P
(2023)
Learning via Wasserstein-Based High Probability Generalisation Bounds
Picard-Weibel A
(2022)
On change of measure inequalities for $f$-divergences
Deligiannidis G
(2019)
Exponential ergodicity of the bouncy particle sampler
in The Annals of Statistics
Deligiannidis G
(2021)
Randomized Hamiltonian Monte Carlo as scaling limit of the bouncy particle sampler and dimension-free convergence rates
in The Annals of Applied Probability
Tadic V
(2020)
Stability of optimal filter higher-order derivatives
in Stochastic Processes and their Applications
Paulin D
(2022)
A 4D-Var method with flow-dependent background covariances for the shallow-water equations
in Statistics and Computing
Maddison C
(2021)
Dual Space Preconditioning for Gradient Descent
in SIAM Journal on Optimization
Xu T
(2020)
An accelerated correlation filter tracker
in Pattern Recognition
Yin H
(2019)
Learning a representation with the block-diagonal structure for pattern classification
in Pattern Analysis and Applications
Leroy A
(2022)
MAGMA: inference and prediction using multi-task Gaussian processes with common mean
in Machine Learning
Deligiannidis G
(2018)
The Correlated Pseudomarginal Method
in Journal of the Royal Statistical Society Series B: Statistical Methodology
Alquier P
(2022)
Estimation of Copulas via Maximum Mean Discrepancy
in Journal of the American Statistical Association
Bouchard-Côté A
(2018)
The Bouncy Particle Sampler: A Nonreversible Rejection-Free Markov Chain Monte Carlo Method
in Journal of the American Statistical Association
Alenlöv J.
(2021)
Pseudo-marginal hamiltonian monte carlo
in Journal of Machine Learning Research
Pérez-Ortiz M.
(2021)
Tighter risk certificates for neural networks
in Journal of Machine Learning Research
Gagnon P
(2020)
Nonreversible Jump Algorithms for Bayesian Nested Model Selection
in Journal of Computational and Graphical Statistics
Sun S
(2022)
Stability-based PAC-Bayes analysis for multi-view learning algorithms
in Information Fusion
Mikhailiuk A
(2022)
Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality
in IEEE Transactions on Multimedia
Wang R
(2021)
Graph Embedding Multi-Kernel Metric Learning for Image Set Classification With Grassmannian Manifold-Valued Features
in IEEE Transactions on Multimedia
Tadic V
(2021)
Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation
in IEEE Transactions on Information Theory
Tadic V
(2019)
Analyticity of Entropy Rates of Continuous-State Hidden Markov Models
in IEEE Transactions on Information Theory
Zhu X
(2021)
Complementary Discriminative Correlation Filters Based on Collaborative Representation for Visual Object Tracking
in IEEE Transactions on Circuits and Systems for Video Technology
Wang R
(2022)
Multiple Riemannian Manifold-Valued Descriptors Based Image Set Classification With Multi-Kernel Metric Learning
in IEEE Transactions on Big Data
Li L
(2021)
Sequential Learning of Principal Curves: Summarizing Data Streams on the Fly.
in Entropy (Basel, Switzerland)
Guedj B
(2021)
Still No Free Lunches: The Price to Pay for Tighter PAC-Bayes Bounds.
in Entropy (Basel, Switzerland)
Haddouche M
(2021)
PAC-Bayes Unleashed: Generalisation Bounds with Unbounded Losses.
in Entropy (Basel, Switzerland)