Jesse C. Cresswell

According to our database, Jesse C. Cresswell authored at least 34 papers between 2021 and 2025.

Collaborative distances:

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

2025

Textual Bayes: Quantifying Uncertainty in LLM-Based Systems.

Brendan Leigh Ross, Noël Vouitsis, Atiyeh Ashari Ghomi, Rasa Hosseinzadeh, Ji Xin, Zhaoyan Liu, Yi Sui, Shiyi Hou, Kin Kwan Leung, Gabriel Loaiza-Ganem, Jesse C. Cresswell

CoRR, June, 2025

CausalPFN: Amortized Causal Effect Estimation via In-Context Learning.

Vahid Balazadeh Meresht, Hamidreza Kamkari, Valentin Thomas, Benson Li, Junwei Ma, Jesse C. Cresswell, Rahul G. Krishnan

CoRR, June, 2025

Trustworthy AI Must Account for Intersectionality.

Jesse C. Cresswell

CoRR, April, 2025

DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse Tasks.

Wei Cui, Tongzi Wu, Jesse C. Cresswell, Yi Sui, Keyvan Golestan

CoRR, March, 2025

Zero-Execution Retrieval-Augmented Configuration Tuning of Spark Applications.

Raunaq Suri, Ilan Gofman, Guangwei Yu, Jesse C. Cresswell

CoRR, March, 2025

Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factuality.

Naihe Feng, Yi Sui, Shiyi Hou, Jesse C. Cresswell, Ga Wu

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation.

Satya Krishna Gorti, Ilan Gofman, Zhaoyan Liu, Jiapeng Wu, Noël Vouitsis, Guangwei Yu, Jesse C. Cresswell, Rasa Hosseinzadeh

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

A Geometric Framework for Understanding Memorization in Generative Models.

Brendan Leigh Ross, Hamidreza Kamkari, Tongzi Wu, Rasa Hosseinzadeh, Zhaoyan Liu, George Stein, Jesse C. Cresswell, Gabriel Loaiza-Ganem

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Conformal Prediction Sets Can Cause Disparate Impact.

Jesse C. Cresswell, Bhargava Kumar, Yi Sui, Mouloud Belbahri

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Augment then Smooth: Reconciling Differential Privacy with Certified Robustness.

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

Trans. Mach. Learn. Res., 2024

Neural Implicit Manifold Learning for Topology-Aware Density Estimation.

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

Trans. Mach. Learn. Res., 2024

Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections.

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

Trans. Mach. Learn. Res., 2024

Inconsistencies In Consistency Models: Better ODE Solving Does Not Imply Better Samples.

Noël Vouitsis, Rasa Hosseinzadeh, Brendan Leigh Ross, Valentin Villecroze, Satya Krishna Gorti, Jesse C. Cresswell, Gabriel Loaiza-Ganem

CoRR, 2024

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation.

Claudius Krause, Michele Faucci Giannelli, Gregor Kasieczka, Benjamin Nachman, Dalila Salamani, David Shih, Anna Zaborowska, Oz Amram, Kerstin Borras, Matthew R. Buckley, Erik Buhmann, Thorsten Buss, Renato Paulo Da Costa Cardoso, Anthony L. Caterini, Nadezda Chernyavskaya, Federico A. G. Corchia, Jesse C. Cresswell, Sascha Diefenbacher, Etienne Dreyer, Vijay Ekambaram, Engin Eren, Florian Ernst, Luigi Favaro, Matteo Franchini, Frank Gaede, Eilam Gross, Shih-Chieh Hsu, Kristina Jaruskova, Benno Käch, Jayant Kalagnanam, Raghav Kansal, Taewoo Kim, Dmitrii Kobylianskii, Anatolii Korol, William Korcari, Dirk Krücker, Katja Krüger, Marco Letizia, Shu Li, Qibin Liu, Xiulong Liu, Gabriel Loaiza-Ganem, Thandikire Madula, Peter McKeown, Isabell-A. Melzer-Pellmann, Vinicius Mikuni, Nam Nguyen, Ayodele Ore, Sofia Palacios Schweitzer, Ian Pang, Kevin Pedro, Tilman Plehn, Witold Pokorski, Huilin Qu, Piyush Raikwar, John A. Raine, Humberto Reyes-González, Lorenzo Rinaldi, Brendan Leigh Ross, Moritz A. W. Scham, Simon Schnake, Chase Shimmin, Eli Shlizerman, Nathalie Soybelman, Mudhakar Srivatsa, Kalliopi Tsolaki, Sofia Vallecorsa, Kyongmin Yeo, Rui Zhang

CoRR, 2024

TabDPT: Scaling Tabular Foundation Models.

Junwei Ma, Valentin Thomas, Rasa Hosseinzadeh, Hamidreza Kamkari, Alex Labach, Jesse C. Cresswell, Keyvan Golestan, Guangwei Yu, Maksims Volkovs, Anthony L. Caterini

CoRR, 2024

Scaling Up Diffusion and Flow-based XGBoost Models.

Jesse C. Cresswell, Taewoo Kim

CoRR, 2024

Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks.

Antoni Kowalczuk, Jan Dubinski, Atiyeh Ashari Ghomi, Yi Sui, George Stein, Jiapeng Wu, Jesse C. Cresswell, Franziska Boenisch, Adam Dziedzic

CoRR, 2024

A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models.

Hamidreza Kamkari, Brendan Leigh Ross, Rasa Hosseinzadeh, Jesse C. Cresswell, Gabriel Loaiza-Ganem

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

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

Conformal Prediction Sets Improve Human Decision Making.

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

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

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

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