Tuesday seminars - Page 2

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

The role of the environment in the dynamics and evolution of microbial populations

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

From data to decisions: knowledge-driven ML in orthopedic surgery

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor
Reasoning and learning in the setting of possibility theory - Overview and perspectives
 
This seminar is part of the seminar series on the thematic focus of uncertainty quantification (Objective 4: Machine learning with quantified uncertainty).
Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

On RL without Lock in Action

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor
Making AI systems more trustworthy through uncertainty disentanglement
 
This seminar is part of the seminar series on the thematic focus of uncertainty quantification (Objective 4: Machine learning with quantified uncertainty).
Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor
Post-Bayesian Machine Learning

This seminar is part of the seminar series on the thematic focus of uncertainty quantification (Objective 4: Machine learning with quantified uncertainty).
Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

Barotropic trends through Barents Sea opening for the period 1975-2021: The underlying physical processes explained using Artificial Intelligence

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

Restoring the Self: Personal LLMs as guardians of human identity and agency for people living with severe communication disorders

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

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). 

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

Adversarial Training Should Be Cast as a Non-Zero-Sum Game

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

Tuesday seminar on a Wednesday.

Feature learning in two-layer neural networks under structured data

Zoom: https://uio.zoom.us/j/65831656210

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

Effector: A Python package for regional explanations

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

AI, scarce resources and climate transition

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

Vine copula-based regression models

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

Learning representations from high-level structures

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

Reinforcement learning for respondent-driven sampling

Time and place: –, Blindern, Niels Henrik Abels hus, Integreat premises, 8th floor

Explaining Bayesian optimization by Shapley values

Time and place: –, Integreat, NHAbel's hus 8th floor

All models are wrong, and sometimes, the optimiser is wrong too!