Niccolò Dalmasso

发表

Predictive Inference of a Wildfire Risk Pipeline in the United States Proposal Track

Niccolò Dalmasso, A. Reinhart, Shamindra Shrotriya, 2019 .

Feature Engineering for Entity Resolution

Niccolò Dalmasso, Robin Mejia, R. Mejia, 2019 .

When the Oracle Misleads: Modeling the Consequences of Using Observable Rather than Potential Outcomes in Risk Assessment Instruments

Alan Mishler, Niccolò Dalmasso, 2021, 2104.01921.

Structural Forecasting for Short-term Tropical Cyclone Intensity Guidance

Ann B. Lee, Kimberly M. Wood, Niccolò Dalmasso, 2022, 2206.00067.

A Flexible Pipeline for Prediction of Tropical Cyclone Paths

C. Schafer, Robin Dunn, Niccolò Dalmasso, 2019, 1906.08832.

Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe

V. Potluru, T. Balch, Renbo Zhao, 2022, ArXiv.

Diagnostics for conditional density models and Bayesian inference algorithms

Rafael Izbicki, Ann B. Lee, Niccolo Dalmasso, 2021, UAI.

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

Ann B. Lee, P. Freeman, A. Malz, 2019, Astron. Comput..

Clarifying the Hubble constant tension with a Bayesian hierarchical model of the local distance ladder

D. Mortlock, S. Feeney, Niccolò Dalmasso, 2017, 1707.00007.

Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations

Rafael Izbicki, Ann B. Lee, Taylor Pospisil, 2019, AISTATS.

Fair When Trained, Unfair When Deployed: Observable Fairness Measures are Unstable in Performative Prediction Settings

Alan Mishler, Niccolò Dalmasso, 2022, ArXiv.

Likelihood-Free Frequentist Inference: Confidence Sets with Correct Conditional Coverage

Ann B. Lee, Rafael Izbicki, Niccolò Dalmasso, 2021, 2107.03920.

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

Ann B. Lee, David Y. Zhao, Rafael Izbicki, 2021, ArXiv.

HECT: High-Dimensional Ensemble Consistency Testing for Climate Models

Dorit Hammerling, Ann B. Lee, Niccolo Dalmasso, 2020, 2010.04051.

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

Ann B. Lee, Rafael Izbicki, Niccolo Dalmasso, 2020, ICML.

Deep Gaussian Mixture Ensembles

Yousef El-Laham, Niccolò Dalmasso, Svitlana Vyetrenko, 2023, Conference on Uncertainty in Artificial Intelligence.

Explicit Group Sparse Projection with Applications to Deep Learning and NMF

Nicolas Gillis, S. Plis, V. Potluru, 2019, Trans. Mach. Learn. Res..

Structural Forecasting for Short-term Tropical Cyclone Intensity Guidance

Ann B. Lee, Kimberly M. Wood, Niccolò Dalmasso, 2022, Weather and forecasting.

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

Ann B. Lee, Trey McNeely, Kimberly M. Wood, 2020, ArXiv.

Differentially Private Learning of Hawkes Processes

V. Potluru, T. Balch, Niccolò Dalmasso, 2022, ArXiv.

Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning for Reliable Simulator-Based Inference

David Y. Zhao, Niccolò Dalmasso, Luca Masserano, 2021, 2107.03920.

Likelihood-Free Frequentist Inference: Conﬁdence Sets with Correct Conditional Coverage Finite-sample conﬁdence sets for known test statistic sets in a likelihood-free inference setting Diagnostics for HEP example with nuisance parameters

Ann B. Lee, Rafael Izbicki, Niccolò Dalmasso, 2022 .

Validating Conditional Density Models and Bayesian Inference Algorithms

Ann B. Lee, David Y. Zhao, Rafael Izbicki, 2021 .

Fair Wasserstein Coresets

Vamsi K. Potluru, T. Balch, Niccolò Dalmasso, 2023, ArXiv.