activity
20192025
most citedQuantifying protocols for safe school activities

3 citations · 4 across the 9 of their papers we have counts for

collaborators

9 papers

stat.ME2025

Extending Prediction-Powered Inference through Conformal Prediction

Daniel Csillag, Pedro Dall'Antonia, Claudio José Struchiner +1

Prediction-powered inference is a recent methodology for the safe use of black-box ML models to impute missing data, strengthening inference of statistical parameters. However, man…

cs.CL2025

Mining Unstructured Medical Texts With Conformal Active Learning

Juliano Genari, Guilherme Tegoni Goedert

The extraction of relevant data from Electronic Health Records (EHRs) is crucial to identifying symptoms and automating epidemiological surveillance processes. By harnessing the va…

cs.CV2025

Image Super-Resolution with Guarantees via Conformalized Generative Models

Eduardo Adame, Daniel Csillag, Guilherme Tegoni Goedert

The increasing use of generative ML foundation models for image restoration tasks such as super-resolution calls for robust and interpretable uncertainty quantification methods. We…

stat.ML2025

Prediction-Powered E-Values

Daniel Csillag, Claudio José Struchiner, Guilherme Tegoni Goedert

Quality statistical inference requires a sufficient amount of data, which can be missing or hard to obtain. To this end, prediction-powered inference has risen as a promising metho…

stat.ML2024

Strategic Conformal Prediction

Daniel Csillag, Claudio José Struchiner, Guilherme Tegoni Goedert

When a machine learning model is deployed, its predictions can alter its environment, as better informed agents strategize to suit their own interests. With such alterations in min…

stat.ML2024

Generalization Bounds for Causal Regression: Insights, Guarantees and Sensitivity Analysis

Daniel Csillag, Claudio José Struchiner, Guilherme Tegoni Goedert

Many algorithms have been recently proposed for causal machine learning. Yet, there is little to no theory on their quality, especially considering finite samples. In this work, we…

physics.flu-dyn2023

Instanton-based Importance Sampling for Extreme Fluctuations in a Shell Model for Turbulent Energy Cascade

Guilherme Tegoni Goedert, Luca Biferale

Many out-of-equilibrium flows present non-Gaussian fluctuations in physically relevant observables, such as energy dissipation rate. This implies extreme fluctuations that, althoug…

physics.soc-ph2022★ 3 cited

Quantifying protocols for safe school activities

Juliano Genari, Guilherme Tegoni Goedert, Sergio H. A. Lira +12

By the peak of COVID-19 restrictions on April 8, 2020, up to 1.5 billion students across 188 countries were by the suspension of physical attendance in schools. Schools were among…

math.AP2019★ 1 cited

Resonance in rarefaction and shock curves: local analysis and numerics of the continuation method

A. C. Alvarez, G. T. Goedert, D. Marchesin

In this paper, we describe certain crucial steps in the development of an algorithm for finding the Riemann solution in systems of conservation laws. We relax the classical hypothe…