Publications | Niccolò (Nic) Dalmasso, PhD

Fair Wasserstein Coresets

Zikai Xiong, Niccolò Dalmasso, Shubham Sharma, Freddy Lecue, Daniele Magazzeni, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

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FairWASP: Fast and optimal fair Wasserstein pre-processing

Zikai Xiong, Niccolò Dalmasso, Alan Mishler, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

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Robust Learning Rate Selection for Stochastic Optimization via Splitting Diagnostic

Matteo Sordello, Niccolò Dalmasso, Hangfeng He, Weijie Su

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Fair Wasserstein Coresets

Zikai Xiong, Niccolò Dalmasso, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

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Efficient Event Series Data Modeling via First-Order Constrained Optimization

Niccolò Dalmasso, Renbo Zhao, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

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Deep Gaussian Mixture Ensembles

Yousef El-Laham, Niccolò Dalmasso, Elizabeth Fons, Svitlana Vyetrenko

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Structural Forecasting for Short-term Tropical Cyclone Intensity Guidance

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

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

Alan Mishler, Niccolò Dalmasso

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

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

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Validating Conditional Density Models and Bayesian Inference Algorithms

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

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PayVAE: A Generative Model for Financial Transactions

Niccolò Dalmasso, Robert E. Tillman, Prashant Reddy, Manuela Veloso

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

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

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HECT: High-Dimensional Ensemble Consistency Testing for Climate Models

Niccolò Dalmasso, Galen Vincent, Dorit Hammerling, Ann B. Lee

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

Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee

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Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations

Complex phenomena are often modeled with computationally intensive feed-forward simulations for which a tractable analytic likelihood …

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

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Predictive Inference of a Wildfire Risk Pipeline in the United States

Niccolò Dalmasso, Shamindra Shrotriya, Alex Reinhart (Equal Contribution)

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Feature Engineering for Entity Resolution with Arabic Names: Improving Estimates of Observed Casualties in the Syrian Civil War

Niccolò Dalmasso, Robin Mejia, Jordan Rodu, Megan Price, Jared S Murray

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

Alan Mishler, Niccolò Dalmasso

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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

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Architectural Distant Reading Using Machine Learning to Identify Typological Traits Across Multiple Buildings

This paper introduces an approach to architectural “distant reading”: the use of computational methods to analyze architectural data in …

Cecilia Ferrando, Niccolò Dalmasso, Jiawei Mai, Daniel Cardoso Llach

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A Flexible Pipeline for Prediction of Tropical Cyclone Paths

We introduce a new pipeline that encourages transparent and adaptable prediction band development by streamlining cyclone track …

Niccolò Dalmasso, Robin Dunn, Benjamin LeRoy, Chad Schafer

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Lebesgue Regression

We propose Lebesgue Regression, a non-parametric high-dimensional regression method that gives prediction sets instead of a single …

Yotam Hechtlinger, Niccolò Dalmasso, Alessandro Rinaldo, Larry Wasserman

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

We have developed a Bayesian hierarchical model of the full distance ladder to assess the H0 discrepancy between the local distance …

Stephen M. Feeney, Daniel J. Mortlock, Niccolò Dalmasso

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