George Deligiannidis

According to our database, George Deligiannidis authored at least 35 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Error Bounds for Flow Matching Methods.

Joe Benton, George Deligiannidis, Arnaud Doucet

Trans. Mach. Learn. Res., 2024

Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions.

Iskander Azangulov, George Deligiannidis, Judith Rousseau

CoRR, 2024

Differentiable Cost-Parameterized Monge Map Estimators.

Samuel Howard, George Deligiannidis, Patrick Rebeschini, James Thornton

CoRR, 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

Particle Denoising Diffusion Sampler.

Angus Phillips, Hai-Dang Dau, Michael John Hutchinson, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization.

Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis

Proceedings of the Twelfth International Conference on Learning Representations, 2024

On the Expected Size of Conformal Prediction Sets.

Guneet S. Dhillon, George Deligiannidis, Tom Rainforth

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Linear Convergence Bounds for Diffusion Models via Stochastic Localization.

Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis

CoRR, 2023

Generalization Bounds with Data-dependent Fractal Dimensions.

Benjamin Dupuis, George Deligiannidis, Umut Simsekli

CoRR, 2023

A Unified Framework for U-Net Design and Analysis.

Christopher Williams, Fabian Falck, George Deligiannidis, Chris C. Holmes, Arnaud Doucet, Saifuddin Syed

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Generalization Bounds using Data-Dependent Fractal Dimensions.

Benjamin Dupuis, George Deligiannidis, Umut Simsekli

Proceedings of the International Conference on Machine Learning, 2023

Wide stochastic networks: Gaussian limit and PAC-Bayesian training.

Eugenio Clerico, George Deligiannidis, Arnaud Doucet

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022

From Denoising Diffusions to Denoising Markov Models.

Joe Benton, Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet

CoRR, 2022

A PAC-Bayes bound for deterministic classifiers.

Eugenio Clerico, George Deligiannidis, Benjamin Guedj, Arnaud Doucet

CoRR, 2022

Ranking in Contextual Multi-Armed Bandits.

Amitis Shidani, George Deligiannidis, Arnaud Doucet

CoRR, 2022

Conditional simulation using diffusion Schrödinger bridges.

Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet

Proceedings of the Uncertainty in Artificial Intelligence, 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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Continuous Time Framework for Discrete Denoising Models.

Andrew Campbell, Joe Benton, Valentin De Bortoli, Thomas Rainforth, George Deligiannidis, Arnaud Doucet

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Chained generalisation bounds.

Eugenio Clerico, Amitis Shidani, George Deligiannidis, Arnaud Doucet

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Neural score matching for high-dimensional causal inference.

Oscar Clivio, Fabian Falck, Brieuc Lehmann, George Deligiannidis, Chris C. Holmes

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Conditionally Gaussian PAC-Bayes.

Eugenio Clerico, George Deligiannidis, Arnaud Doucet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

On Mixing Times of Metropolized Algorithm With Optimization Step (MAO) : A New Framework.

E. L. Mahdi Khribch, George Deligiannidis, Daniel Paulin

CoRR, 2021

Conditional Gaussian PAC-Bayes.

Eugenio Clerico, George Deligiannidis, Arnaud Doucet

CoRR, 2021

Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure.

George Deligiannidis, Valentin De Bortoli, Arnaud Doucet

CoRR, 2021

Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms.

Alexander Camuto, George Deligiannidis, Murat A. Erdogdu, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentiable Particle Filtering via Entropy-Regularized Optimal Transport.

Adrien Corenflos, James Thornton, George Deligiannidis, Arnaud Doucet

Proceedings of the 38th International Conference on Machine Learning, 2021

Stable ResNet.

Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Hausdorff Dimension, Stochastic Differential Equations, and Generalization in Neural Networks.

Umut Simsekli, Ozan Sener, George Deligiannidis, Murat A. Erdogdu

CoRR, 2020

Random walk algorithm for the Dirichlet problem for parabolic integro-differential equation.

George Deligiannidis, S. Maurer, Michael V. Tretyakov

CoRR, 2020

Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks.

Umut Simsekli, Ozan Sener, George Deligiannidis, Murat A. Erdogdu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows.

Robert Cornish, Anthony L. Caterini, George Deligiannidis, Arnaud Doucet

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Localised Generative Flows.

Robert Cornish, Anthony L. Caterini, George Deligiannidis, Arnaud Doucet

CoRR, 2019

Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets.

Robert Cornish, Paul Vanetti, Alexandre Bouchard-Côté, George Deligiannidis, Arnaud Doucet

Proceedings of the 36th International Conference on Machine Learning, 2019

Bernoulli Race Particle Filters.

Sebastian M. Schmon, Arnaud Doucet, George Deligiannidis

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Unbiased Smoothing using Particle Independent Metropolis-Hastings.

Lawrece Middleton, George Deligiannidis, Arnaud Doucet, Pierre E. Jacob

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019