Richard Bergna

Joined

August 2023

Names

Richard Bergna (Preferred)

Emails

****@gmail.com (Confirmed)

Personal Links

Career & Education History

MS student

University of Cambridge (cam.ac.uk)

2022 – 2023

Undergrad student

University of Bristol (bristol.ac.uk)

2018 – 2021

Advisors, Relations & Conflicts

Coauthor

Felix Opolka

2023 – 2023

Coauthor

Pietro Liò

2023 – 2023

Coauthor

Jose Miguel Hernandez-Lobato

2023 – 2023

Expertise

No areas of expertise listed

Publications

A Gaussian Process View on Observation Noise and Initialization in Wide Neural Networks
Sergio Calvo Ordoñez, Jonathan Plenk, Richard Bergna, Alvaro Cartea, José Miguel Hernández-Lobato, Konstantina Palla, Kamil Ciosek
- AISTATS 2026 Poster
- Readers: Everyone
GAPA: Post-Hoc Uncertainty Quantification for Pre-Trained Models via Activation-Space Gaussian Processes
Richard Bergna, Stefan Depeweg, Sergio Calvo Ordoñez, Jonathan Plenk, Alvaro Cartea, José Miguel Hernández-Lobato
- ICLR 2026 Conference Desk Rejected Submission
- Readers: Everyone
Observation Noise and Initialization in Wide Neural Networks
Sergio Calvo Ordoñez, Jonathan Plenk, Richard Bergna, Alvaro Cartea, José Miguel Hernández-Lobato, Konstantina Palla, Kamil Ciosek
- AABI 2025 Workshop Track
- Readers: Everyone
Post-Hoc Uncertainty Quantification in Pre-Trained Neural Networks via Activation-Level Gaussian Processes
Richard Bergna, Stefan Depeweg, Sergio Calvo Ordoñez, Jonathan Plenk, Alvaro Cartea, José Miguel Hernández-Lobato
- AABI 2025 Workshop Track
- Readers: Everyone
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
Richard Bergna, Sergio Calvo Ordoñez, Felix Opolka, Pietro Lio, José Miguel Hernández-Lobato
- ICLR 2025 Spotlight
- Readers: Everyone
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
Richard Bergna, Sergio Calvo Ordoñez, Felix Opolka, Pietro Lio, José Miguel Hernández-Lobato
- NeurIPS BDU Workshop 2024 Poster
- Readers: Everyone

Richard Bergna

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

A Gaussian Process View on Observation Noise and Initialization in Wide Neural Networks

GAPA: Post-Hoc Uncertainty Quantification for Pre-Trained Models via Activation-Space Gaussian Processes

Observation Noise and Initialization in Wide Neural Networks

Post-Hoc Uncertainty Quantification in Pre-Trained Neural Networks via Activation-Level Gaussian Processes

Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations

Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations

Co-Authors