George Deligiannidis

Orcid: 0000-0002-0821-4607

According to our database1, George Deligiannidis authored at least 36 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Error Bounds for Flow Matching Methods.
Trans. Mach. Learn. Res., 2024

Linear Convergence of Diffusion Models Under the Manifold Hypothesis.
CoRR, 2024

Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions.
CoRR, 2024

Differentiable Cost-Parameterized Monge Map Estimators.
CoRR, 2024

Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets.
CoRR, 2024

Particle Denoising Diffusion Sampler.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

On the Expected Size of Conformal Prediction Sets.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Linear Convergence Bounds for Diffusion Models via Stochastic Localization.
CoRR, 2023

Generalization Bounds with Data-dependent Fractal Dimensions.
CoRR, 2023

A Unified Framework for U-Net Design and Analysis.
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.
Proceedings of the International Conference on Machine Learning, 2023

Wide stochastic networks: Gaussian limit and PAC-Bayesian training.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022
From Denoising Diffusions to Denoising Markov Models.
CoRR, 2022

A PAC-Bayes bound for deterministic classifiers.
CoRR, 2022

Ranking in Contextual Multi-Armed Bandits.
CoRR, 2022

Conditional simulation using diffusion Schrödinger bridges.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs.
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.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Neural score matching for high-dimensional causal inference.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Conditionally Gaussian PAC-Bayes.
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.
CoRR, 2021

Conditional Gaussian PAC-Bayes.
CoRR, 2021

Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure.
CoRR, 2021

Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021

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

2020
Hausdorff Dimension, Stochastic Differential Equations, and Generalization in Neural Networks.
CoRR, 2020

Random walk algorithm for the Dirichlet problem for parabolic integro-differential equation.
CoRR, 2020

Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks.
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.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Localised Generative Flows.
CoRR, 2019

Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets.
Proceedings of the 36th International Conference on Machine Learning, 2019

Bernoulli Race Particle Filters.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Unbiased Smoothing using Particle Independent Metropolis-Hastings.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019


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