Alek Fröhlich

PhD student, Computer Science, Università degli Studi di Genova, Istituto Italiano di Tecnologia

Joined

August 2024

Names

Alek Fröhlich (Preferred)

Emails

****@posgrad.ufsc.br (Confirmed)

****@iit.it (Confirmed)

Personal Links

Homepage

Google Scholar

DBLP

Career & Education History

PhD student

Computer Science, Università degli Studi di Genova, Istituto Italiano di Tecnologia (iit.it)

2024 – 2027

MS student

Mathematics, Universidade Federal de Santa Catarina (ufsc.br)

2022 – 2024

Undergrad student

Computer Science, Universidade Federal de Santa Catarina (ufsc.br)

2018 – 2022

Advisors, Relations & Conflicts

PhD Advisor

Massimiliano Pontil

Present

Expertise

No areas of expertise listed

Publications

Drift-Aware Uncertainty Quantification via a Functional Spectral-Newton Method
Thiago Ramos, Alek Fröhlich, Daniel Perazzo, Massimiliano Pontil
- CAO Poster
- Readers: Everyone
Outcome-Aware Spectral Feature Learning for Instrumental Variable Regression
Dimitri Meunier, Jakub Wornbard, Vladimir R Kostic, Antoine Moulin, Karim Lounici, Alek Fröhlich, Massimiliano Pontil, Arthur Gretton
- Submitted to ICLR 2026
- Readers: Everyone
Representation Learning for Equivariant Inference with Guarantees
Daniel Ordonez-Apraez, Vladimir R Kostic, Alek Fröhlich, Vivien Brandt, Karim Lounici, Massimiliano Pontil
- ICLR 2026 Conference Desk Rejected Submission
- Readers: Everyone
Unifying Regression and Uncertainty Quantification with Contrastive Spectral Representation Learning
Daniel Ordonez-Apraez, Vladimir R Kostic, Alek Fröhlich, Karim Lounici, Massimiliano Pontil
- NeurReps 2025 Poster
- Readers: Everyone
Equivariant Representation Learning for Symmetry-Aware Inference with Guarantees
Daniel Ordonez-Apraez, Vladimir R Kostic, Alek Fröhlich, Karim Lounici, Massimiliano Pontil
- CoRL 2025 Robot Data Workshop
- Readers: Everyone
Equivariant Representation Learning for Symmetry-Aware Inference with Guarantees
Daniel Ordonez-Apraez, Vladimir R Kostic, Alek Fröhlich, Karim Lounici, Massimiliano Pontil
- SAFE-ROL Poster
- Readers: Everyone
PersonalizedUS: Interpretable Breast Cancer Risk Assessment with Local Coverage Uncertainty Quantification
Alek Fröhlich, Thiago Ramos, Gustavo Motta Cabello Dos Santos, Isabela Panzeri Carlotti Buzatto, Rafael Izbicki, Daniel Guimarães Tiezzi
- AAAI 2025
- Readers: Everyone

Alek Fröhlich

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Drift-Aware Uncertainty Quantification via a Functional Spectral-Newton Method

Outcome-Aware Spectral Feature Learning for Instrumental Variable Regression

Representation Learning for Equivariant Inference with Guarantees

Unifying Regression and Uncertainty Quantification with Contrastive Spectral Representation Learning

Equivariant Representation Learning for Symmetry-Aware Inference with Guarantees

Equivariant Representation Learning for Symmetry-Aware Inference with Guarantees

PersonalizedUS: Interpretable Breast Cancer Risk Assessment with Local Coverage Uncertainty Quantification

Co-Authors