Ann B. Lee

According to our database, Ann B. Lee authored at least 21 papers between 2000 and 2024.

Collaborative distances:

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

2024

Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference.

Luca Masserano, Alexander Shen, Michele Doro, Tommaso Dorigo, Rafael Izbicki, Ann B. Lee

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

2023

Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems.

Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Simulation-Based Inference with WALDO: Perfectly Calibrated Confidence Regions Using Any Prediction or Posterior Estimation Algorithm.

Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee

CoRR, 2022

Calibrated Predictive Distributions via Diagnostics for Conditional Coverage.

Biprateep Dey, David Zhao, Jeffrey A. Newman, Brett H. Andrews, Rafael Izbicki, Ann B. Lee

CoRR, 2022

2021

Re-calibrating Photometric Redshift Probability Distributions Using Feature-space Regression.

Biprateep Dey, Jeffrey A. Newman, Brett H. Andrews, Rafael Izbicki, Ann B. Lee, David Zhao, Markus Michael Rau, Alex I. Malz

CoRR, 2021

Identifying Distributional Differences in Convective Evolution Prior to Rapid Intensification in Tropical Cyclones.

Trey McNeely, Galen Vincent, Rafael Izbicki, Kimberly M. Wood, Ann B. Lee

CoRR, 2021

Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning in Simulation and Uncertainty Quantification.

Niccolò Dalmasso, David Zhao, Rafael Izbicki, Ann B. Lee

CoRR, 2021

Diagnostics for conditional density models and Bayesian inference algorithms.

David Zhao, Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Structural Forecasting for Tropical Cyclone Intensity Prediction: Providing Insight with Deep Learning.

Trey McNeely, Niccolò Dalmasso, Kimberly M. Wood, Ann B. Lee

CoRR, 2020

Conditional density estimation tools in python and R with applications to photometric redshifts and likelihood-free cosmological inference.

Niccolò Dalmasso, Taylor Pospisil, Ann B. Lee, Rafael Izbicki, Peter E. Freeman, Alex I. Malz

Astron. Comput., 2020

Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting.

Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee

Proceedings of the 37th International Conference on Machine Learning, 2020

Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations.

Niccolò Dalmasso, Ann B. Lee, Rafael Izbicki, Taylor Pospisil, Ilmun Kim, Chieh-An Lin

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2018

RFCDE: Random Forests for Conditional Density Estimation.

Taylor Pospisil, Ann B. Lee

CoRR, 2018

2014

High-Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation.

Rafael Izbicki, Ann B. Lee, Chad Schafer

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2011

An Optimal Transportation Approach for Nuclear Structure-Based Pathology.

Wei Wang, John A. Ozolek, Dejan Slepcev, Ann B. Lee, Cheng Chen, Gustavo K. Rohde

IEEE Trans. Medical Imaging, 2011

2007

Treelets | A Tool for Dimensionality Reduction and Multi-Scale Analysis of Unstructured Data.

Ann B. Lee, Boaz Nadler

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

2006

Diffusion Maps and Coarse-Graining: A Unified Framework for Dimensionality Reduction, Graph Partitioning, and Data Set Parameterization.

Stéphane Lafon, Ann B. Lee

IEEE Trans. Pattern Anal. Mach. Intell., 2006

2003

The Nonlinear Statistics of High-Contrast Patches in Natural Images.

Ann B. Lee, Kim Steenstrup Pedersen, David Mumford

Int. J. Comput. Vis., 2003

2002

Toward a Full Probability Model of Edges in Natural Images.

Kim Steenstrup Pedersen, Ann B. Lee

Proceedings of the Computer Vision, 2002

2001

Occlusion Models for Natural Images: A Statistical Study of a Scale-Invariant Dead Leaves Model.

Ann B. Lee, David Mumford, Jinggang Huang

Int. J. Comput. Vis., 2001

2000

Statistics of Range Images.

Jinggang Huang, Ann B. Lee, David Mumford

Proceedings of the 2000 Conference on Computer Vision and Pattern Recognition (CVPR 2000), 2000