2024
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Using AI to dampen the unpredictability brought by climate change
This seminar is part of the seminar series on the thematic focus of sustainability (Objective 3: Fair, Explainable, and Trustworthy Learning).
Green AI
Adversarial Training Should Be Cast as a Non-Zero-Sum Game
Making AI sustainable
Tuesday seminar on a Wednesday.
Feature learning in two-layer neural networks under structured data
Zoom: https://uio.zoom.us/j/65831656210
Effector: A Python package for regional explanations
AI, scarce resources and climate transition
Vine copula-based regression models
Learning representations from high-level structures
Reinforcement learning for respondent-driven sampling
Explaining Bayesian optimization by Shapley values
The Bayesian learning rule
All models are wrong, and sometimes, the optimiser is wrong too!
This seminar is part of the seminar series on Integreat's objective Fair, Explainable and Trustworthy Machine Learning.
Dr. Rami Mochaourab research leader of Research Institutes of Sweden RISE gives a brief overview of trustworthy AI and delves into aspects of trustworthiness: accuracy, privacy, and explainability.