Jesse C. Cresswell

According to our database, Jesse C. Cresswell authored at least 17 papers between 2021 and 2024.

Collaborative distances:

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

2024

A Geometric Explanation of the Likelihood OOD Detection Paradox.

Hamidreza Kamkari, Brendan Leigh Ross, Jesse C. Cresswell, Anthony L. Caterini, Rahul G. Krishnan, Gabriel Loaiza-Ganem

CoRR, 2024

Conformal Prediction Sets Improve Human Decision Making.

Jesse C. Cresswell, Yi Sui, Bhargava Kumar, Noël Vouitsis

CoRR, 2024

2023

Data-Efficient Multimodal Fusion on a Single GPU.

Noël Vouitsis, Zhaoyan Liu, Satya Krishna Gorti, Valentin Villecroze, Jesse C. Cresswell, Guangwei Yu, Gabriel Loaiza-Ganem, Maksims Volkovs

CoRR, 2023

Self-supervised Representation Learning From Random Data Projectors.

Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs

CoRR, 2023

Augment then Smooth: Reconciling Differential Privacy with Certified Robustness.

Jiapeng Wu, Atiyeh Ashari Ghomi, David Glukhov, Jesse C. Cresswell, Franziska Boenisch, Nicolas Papernot

CoRR, 2023

Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models.

George Stein, Jesse C. Cresswell, Rasa Hosseinzadeh, Yi Sui, Brendan Leigh Ross, Valentin Villecroze, Zhaoyan Liu, Anthony L. Caterini, J. Eric T. Taylor, Gabriel Loaiza-Ganem

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

Disparate Impact in Differential Privacy from Gradient Misalignment.

Maria S. Esipova, Atiyeh Ashari Ghomi, Yaqiao Luo, Jesse C. Cresswell

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Verifying the Union of Manifolds Hypothesis for Image Data.

Bradley C. A. Brown, Anthony L. Caterini, Brendan Leigh Ross, Jesse C. Cresswell, Gabriel Loaiza-Ganem

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Diagnosing and Fixing Manifold Overfitting in Deep Generative Models.

Gabriel Loaiza-Ganem, Brendan Leigh Ross, Jesse C. Cresswell, Anthony L. Caterini

Trans. Mach. Learn. Res., 2022

CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds.

Jesse C. Cresswell, Brendan Leigh Ross, Gabriel Loaiza-Ganem, Humberto Reyes-González, Marco Letizia, Anthony L. Caterini

CoRR, 2022

Find Your Friends: Personalized Federated Learning with the Right Collaborators.

Yi Sui, Junfeng Wen, Yenson Lau, Brendan Leigh Ross, Jesse C. Cresswell

CoRR, 2022

The Union of Manifolds Hypothesis and its Implications for Deep Generative Modelling.

Bradley C. A. Brown, Anthony L. Caterini, Brendan Leigh Ross, Jesse C. Cresswell, Gabriel Loaiza-Ganem

CoRR, 2022

Neural Implicit Manifold Learning for Topology-Aware Generative Modelling.

Brendan Leigh Ross, Gabriel Loaiza-Ganem, Anthony L. Caterini, Jesse C. Cresswell

CoRR, 2022

Denoising Deep Generative Models.

Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham, Jesse C. Cresswell, Anthony L. Caterini

Proceedings of the Proceedings on "I Can't Believe It's Not Better!, 2022

2021

ProxyFL: Decentralized Federated Learning through Proxy Model Sharing.

Shivam Kalra, Junfeng Wen, Jesse C. Cresswell, Maksims Volkovs, Hamid R. Tizhoosh

CoRR, 2021

Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows.

Brendan Leigh Ross, Jesse C. Cresswell

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

C-Learning: Horizon-Aware Cumulative Accessibility Estimation.

Panteha Naderian, Gabriel Loaiza-Ganem, Harry J. Braviner, Anthony L. Caterini, Jesse C. Cresswell, Tong Li, Animesh Garg

Proceedings of the 9th International Conference on Learning Representations, 2021