Unbiased Smoothing using Particle Independent Metropolis-Hastings. - Lawrece Middleton; George Deligiannidis; Arnaud Doucet; Pierre E. Jacob (AISTATS, 2019)

Bernoulli Race Particle Filters. - Sebastian M. Schmon; Arnaud Doucet; George Deligiannidis (AISTATS, 2019)

Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets. - Robert Cornish; Paul Vanetti; Alexandre Bouchard-Côté; George Deligiannidis; Arnaud Doucet (ICML, 2019)

Localised Generative Flows. - Robert Cornish; Anthony L. Caterini; George Deligiannidis; Arnaud Doucet (CoRR, 2019)

Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows. - Robert Cornish; Anthony L. Caterini; George Deligiannidis; Arnaud Doucet (ICML, 2020)

Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks. - Umut Simsekli; Ozan Sener; George Deligiannidis; Murat A. Erdogdu (NeurIPS, 2020)

Random walk algorithm for the Dirichlet problem for parabolic integro-differential equation. - George Deligiannidis; S. Maurer; Michael V. Tretyakov (CoRR, 2020)

Hausdorff Dimension, Stochastic Differential Equations, and Generalization in Neural Networks. - Umut Simsekli; Ozan Sener; George Deligiannidis; Murat A. Erdogdu (CoRR, 2020)

Stable ResNet. - Soufiane Hayou; Eugenio Clerico; Bobby He; George Deligiannidis; Arnaud Doucet; Judith Rousseau (AISTATS, 2021)

Differentiable Particle Filtering via Entropy-Regularized Optimal Transport. - Adrien Corenflos; James Thornton; George Deligiannidis; Arnaud Doucet (ICML, 2021)

Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. - Alexander Camuto; George Deligiannidis; Murat A. Erdogdu; Mert Gürbüzbalaban; Umut Simsekli; Lingjiong Zhu (NeurIPS, 2021)

Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure. - George Deligiannidis; Valentin De Bortoli; Arnaud Doucet (CoRR, 2021)

Conditional Gaussian PAC-Bayes. - Eugenio Clerico; George Deligiannidis; Arnaud Doucet (CoRR, 2021)

On Mixing Times of Metropolized Algorithm With Optimization Step (MAO) : A New Framework. - E. L. Mahdi Khribch; George Deligiannidis; Daniel Paulin (CoRR, 2021)

Conditionally Gaussian PAC-Bayes. - Eugenio Clerico; George Deligiannidis; Arnaud Doucet (AISTATS, 2022)

Neural score matching for high-dimensional causal inference. - Oscar Clivio; Fabian Falck; Brieuc Lehmann; George Deligiannidis; Chris C. Holmes (AISTATS, 2022)

Chained generalisation bounds. - Eugenio Clerico; Amitis Shidani; George Deligiannidis; Arnaud Doucet (COLT, 2022)

A Continuous Time Framework for Discrete Denoising Models. - Andrew Campbell; Joe Benton; Valentin De Bortoli; Thomas Rainforth; George Deligiannidis; Arnaud Doucet (NeurIPS, 2022)

A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. - Fabian Falck; Christopher Williams; Dominic Danks; George Deligiannidis; Christopher Yau; Chris C. Holmes; Arnaud Doucet; Matthew Willetts (NeurIPS, 2022)

Conditional simulation using diffusion Schrödinger bridges. - Yuyang Shi 002; Valentin De Bortoli; George Deligiannidis; Arnaud Doucet (UAI, 2022)

Ranking in Contextual Multi-Armed Bandits. - Amitis Shidani; George Deligiannidis; Arnaud Doucet (CoRR, 2022)

A PAC-Bayes bound for deterministic classifiers. - Eugenio Clerico; George Deligiannidis; Benjamin Guedj; Arnaud Doucet (CoRR, 2022)

From Denoising Diffusions to Denoising Markov Models. - Joe Benton; Yuyang Shi 002; Valentin De Bortoli; George Deligiannidis; Arnaud Doucet (CoRR, 2022)

Wide stochastic networks: Gaussian limit and PAC-Bayesian training. - Eugenio Clerico; George Deligiannidis; Arnaud Doucet (ALT, 2023)

Generalization Bounds using Data-Dependent Fractal Dimensions. - Benjamin Dupuis; George Deligiannidis; Umut Simsekli (ICML, 2023)

A Unified Framework for U-Net Design and Analysis. - Christopher Williams; Fabian Falck; George Deligiannidis; Chris C. Holmes; Arnaud Doucet; Saifuddin Syed (NeurIPS, 2023)

Generalization Bounds with Data-dependent Fractal Dimensions. - Benjamin Dupuis; George Deligiannidis; Umut Simsekli (CoRR, 2023)

Linear Convergence Bounds for Diffusion Models via Stochastic Localization. - Joe Benton; Valentin De Bortoli; Arnaud Doucet; George Deligiannidis (CoRR, 2023)

On the Expected Size of Conformal Prediction Sets. - Guneet S. Dhillon; George Deligiannidis; Tom Rainforth (AISTATS, 2024)

Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization. - Joe Benton; Valentin De Bortoli; Arnaud Doucet; George Deligiannidis (ICLR, 2024)

Particle Denoising Diffusion Sampler. - Angus Phillips; Hai-Dang Dau; Michael John Hutchinson; Valentin De Bortoli; George Deligiannidis; Arnaud Doucet (ICML, 2024)

Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets. - Benjamin Dupuis; Paul Viallard; George Deligiannidis; Umut Simsekli (CoRR, 2024)

Differentiable Cost-Parameterized Monge Map Estimators. - Samuel Howard; George Deligiannidis; Patrick Rebeschini; James Thornton (CoRR, 2024)

Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions. - Iskander Azangulov; George Deligiannidis; Judith Rousseau (CoRR, 2024)

Error Bounds for Flow Matching Methods. - Joe Benton; George Deligiannidis; Arnaud Doucet (Trans. Mach. Learn. Res., 2024)

Generalisation under gradient descent via deterministic PAC-Bayes. - Eugenio Clerico; Tyler Farghly; George Deligiannidis; Benjamin Guedj; Arnaud Doucet (ALT, 2025)

Linear Convergence of Diffusion Models Under the Manifold Hypothesis. - Peter Potaptchik; Iskander Azangulov; George Deligiannidis (COLT, 2025)

Understanding the Generalization Error of Markov algorithms through Poissonization. - Benjamin Dupuis; Maxime Haddouche; George Deligiannidis; Umut Simsekli (CoRR, 2025)

Conditioning Diffusions Using Malliavin Calculus. - Jakiw Pidstrigach; Elizabeth Baker; Carles Domingo-Enrich; George Deligiannidis; Nikolas Nüsken (CoRR, 2025)

Adaptive Diffusion Guidance via Stochastic Optimal Control. - Iskander Azangulov; Peter Potaptchik; Qinyu Li; Eddie Aamari; George Deligiannidis; Judith Rousseau (CoRR, 2025)

Rao-Blackwellised Reparameterisation Gradients. - Kevin Lam; Thang Bui; George Deligiannidis; Yee Whye Teh (CoRR, 2025)

Schrödinger Bridge Matching for Tree-Structured Costs and Entropic Wasserstein Barycentres. - Samuel Howard; Peter Potaptchik; George Deligiannidis (CoRR, 2025)

Implicit Regularisation in Diffusion Models: An Algorithm-Dependent Generalisation Analysis. - Tyler Farghly; Patrick Rebeschini; George Deligiannidis; Arnaud Doucet (CoRR, 2025)