Jeremiah Birrell

According to our database, Jeremiah Birrell authored at least 17 papers between 2015 and 2025.

Collaborative distances:

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

2025

Concentration Inequalities for the Stochastic Optimization of Unbounded Objectives with Application to Denoising Score Matching.

Jeremiah Birrell

CoRR, February, 2025

Statistical Error Bounds for GANs with Nonlinear Objective Functionals.

Jeremiah Birrell

Trans. Mach. Learn. Res., 2025

An Interactive Framework for Implementing Privacy-Preserving Federated Learning: Experiments on Large Language Models.

Kasra Ahmadi, Rouzbeh Behnia, Reza Ebrahimi, Mehran Mozaffari Kermani, Jeremiah Birrell, Jason Pacheco, Attila A. Yavuz

Proceedings of the 2025 IEEE Security and Privacy, 2025

2024

Concentration Inequalities for (f,Ɣ)-GANs.

Jeremiah Birrell

CoRR, 2024

Nonlinear denoising score matching for enhanced learning of structured distributions.

Jeremiah Birrell, Markos A. Katsoulakis, Luc Rey-Bellet, Benjamin J. Zhang, Wei Zhu

CoRR, 2024

Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement.

Jeremiah Birrell, Reza Ebrahimi, Rouzbeh Behnia, Jason Pacheco

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Adversarially Robust Deep Learning with Optimal-Transport-Regularized Divergences.

Jeremiah Birrell, Reza Ebrahimi

CoRR, 2023

Function-space regularized Rényi divergences.

Jeremiah Birrell, Yannis Pantazis, Paul Dupuis, Luc Rey-Bellet, Markos A. Katsoulakis

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Optimizing Variational Representations of Divergences and Accelerating Their Statistical Estimation.

Jeremiah Birrell, Markos A. Katsoulakis, Yannis Pantazis

IEEE Trans. Inf. Theory, 2022

(f, Gamma)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics.

Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Yannis Pantazis, Luc Rey-Bellet

J. Mach. Learn. Res., 2022

Structure-preserving GANs.

Jeremiah Birrell, Markos A. Katsoulakis, Luc Rey-Bellet, Wei Zhu

Proceedings of the International Conference on Machine Learning, 2022

2021

Variational Representations and Neural Network Estimation of Rényi Divergences.

Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang

SIAM J. Math. Data Sci., 2021

2020

Uncertainty Quantification for Markov Processes via Variational Principles and Functional Inequalities.

Jeremiah Birrell, Luc Rey-Bellet

SIAM/ASA J. Uncertain. Quantification, 2020

(f, Γ)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics.

Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Yannis Pantazis, Luc Rey-Bellet

CoRR, 2020

A Variational Formula for Rényi Divergences.

Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang

CoRR, 2020

2019

Robustness of Dynamical Quantities of Interest via Goal-Oriented Information Theory.

Jeremiah Birrell, Markos A. Katsoulakis, Luc Rey-Bellet

CoRR, 2019

2015

Boltzmann equation solver adapted to emergent chemical non-equilibrium.

Jeremiah Birrell, Jon Wilkening, Johann Rafelski

J. Comput. Phys., 2015