Deligiannidis, George

30 publications

ICML 2025 Conditioning Diffusions Using Malliavin Calculus Jakiw Pidstrigach, Elizabeth Louise Baker, Carles Domingo-Enrich, George Deligiannidis, Nikolas Nüsken

NeurIPS 2025 Diffusion Models and the Manifold Hypothesis: Log-Domain Smoothing Is Geometry Adaptive Tyler Farghly, Peter Potaptchik, Samuel Howard, George Deligiannidis, Jakiw Pidstrigach

ALT 2025 Generalisation Under Gradient Descent via Deterministic PAC-Bayes Eugenio Clerico, Tyler Farghly, George Deligiannidis, Benjamin Guedj, Arnaud Doucet

ICLRW 2025 Generalised Parallel Tempering: Flexible Replica Exchange via Flows and Diffusions Leo Zhang, Peter Potaptchik, George Deligiannidis, Arnaud Doucet, Hai-Dang Dau, Saifuddin Syed

COLT 2025 Linear Convergence of Diffusion Models Under the Manifold Hypothesis Peter Potaptchik, Iskander Azangulov, George Deligiannidis

NeurIPS 2025 Rao-Blackwellised Reparameterisation Gradients Kevin H. Lam, Thang D Bui, George Deligiannidis, Yee Whye Teh

NeurIPS 2025 Schrödinger Bridge Matching for Tree-Structured Costs and Entropic Wasserstein Barycentres Samuel Howard, Peter Potaptchik, George Deligiannidis

ICMLW 2024 Differentiable Cost-Parameterized Monge mAP Estimators Samuel Howard, George Deligiannidis, Patrick Rebeschini, James Thornton

TMLR 2024 Error Bounds for Flow Matching Methods Joe Benton, George Deligiannidis, Arnaud Doucet

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

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

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

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

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

ICML 2023 Generalization Bounds Using Data-Dependent Fractal Dimensions Benjamin Dupuis, George Deligiannidis, Umut Simsekli

ALT 2023 Wide Stochastic Networks: Gaussian Limit and PAC-Bayesian Training Eugenio Clerico, George Deligiannidis, Arnaud Doucet

AISTATS 2022 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 Holmes

NeurIPS 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 K. I. Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C Holmes, Arnaud Doucet, Matthew Willetts

COLT 2022 Chained Generalisation Bounds Eugenio Clerico, Amitis Shidani, George Deligiannidis, Arnaud Doucet

UAI 2022 Conditional Simulation Using Diffusion Schrödinger Bridges Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet

AISTATS 2021 Stable ResNet Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau

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

NeurIPS 2021 Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms Alexander Camuto, George Deligiannidis, Murat A Erdogdu, Mert Gurbuzbalaban, Umut Simsekli, Lingjiong Zhu

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

ICML 2020 Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows Rob Cornish, Anthony Caterini, George Deligiannidis, Arnaud Doucet

AISTATS 2019 Bernoulli Race Particle Filters Sebastian M. Schmon, Arnaud Doucet, George Deligiannidis

ICML 2019 Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets Rob Cornish, Paul Vanetti, Alexandre Bouchard-Cote, George Deligiannidis, Arnaud Doucet

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