Jesse C. Cresswell

Orcid: 0000-0002-9284-8804

According to our database1, Jesse C. Cresswell authored at least 26 papers between 2021 and 2024.

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

Timeline

Legend:

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Online presence:

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Bibliography

2024
Augment then Smooth: Reconciling Differential Privacy with Certified Robustness.
Trans. Mach. Learn. Res., 2024

Neural Implicit Manifold Learning for Topology-Aware Density Estimation.
Trans. Mach. Learn. Res., 2024

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation.
CoRR, 2024

TabDPT: Scaling Tabular Foundation Models.
CoRR, 2024

MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation.
CoRR, 2024

Conformal Prediction Sets Can Cause Disparate Impact.
CoRR, 2024

Scaling Up Diffusion and Flow-based XGBoost Models.
CoRR, 2024

Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks.
CoRR, 2024

A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models.
CoRR, 2024

Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections.
CoRR, 2024

A Geometric Explanation of the Likelihood OOD Detection Paradox.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Conformal Prediction Sets Improve Human Decision Making.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Self-supervised Representation Learning from Random Data Projectors.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Data-Efficient Multimodal Fusion on a Single GPU.
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.
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.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Verifying the Union of Manifolds Hypothesis for Image Data.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Diagnosing and Fixing Manifold Overfitting in Deep Generative Models.
Trans. Mach. Learn. Res., 2022

CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds.
CoRR, 2022

Find Your Friends: Personalized Federated Learning with the Right Collaborators.
CoRR, 2022

The Union of Manifolds Hypothesis and its Implications for Deep Generative Modelling.
CoRR, 2022

Neural Implicit Manifold Learning for Topology-Aware Generative Modelling.
CoRR, 2022

Denoising Deep Generative Models.
Proceedings of the Proceedings on "I Can't Believe It's Not Better!, 2022

2021
ProxyFL: Decentralized Federated Learning through Proxy Model Sharing.
CoRR, 2021

Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows.
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.
Proceedings of the 9th International Conference on Learning Representations, 2021


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