Public events - Page 2

A dual challenge of epistemic justification and political legitimacy

Efficient Likelihood-free Monte Carlo Sampling for Generalized Bayesian Inference Using Probabilistic Surrogate Loss

Integreat researchers present how they use AI for coding and reasearch.

Simulation-based model selection for causal effect estimation

Reading Duede, Eamon. "Instruments, agents, and artificial intelligence: novel epistemic categories of reliability." Synthese 200, no. 6 (2022): 491.

Shaping GNNs with dynamical systems

Using formal verification for text-to-SQL

Generalised mixed effects models for changepoint analysis of biomedical time series

High dimensional regression methods for inhomogeneous Poisson processes via split-variational inference

Causal inference in high-dimensional exploratory experiments 

Register always matters: analysis of LLM pretraining data through the lens of language variation

The unseen frontier: pushing the limits of LLM sparsity with surrogate-free ADMM

Welcome to this week's lunch seminar with August Arnstad and Sigurd Holmsen, PhD Candidates at Integreat – Norwegian Centre for Knowledge-Driven Machine Learning. They will introduce the centre and their current work.

Welcome to the annual Data Science Day, where the data science community comes together for a productive mix of networking, learning, and entertainment. This year we ask: what does AI mean for the way organisations and industries work, and how is it transforming our everyday practices? Through emerging trends, real-world use cases, and forward-looking insights, we’ll explore how intelligent systems are reshaping the workplace—driving efficiency, sparking innovation, and redefining the future of work.

Explainable AI for time series - a signal processing approach

Evading AI systems

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

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

Norwegian Minister of Digitalisation and Public Governance Karianne Tung holds annual lecture on digitalisation status in Norway. 

Coverage correlation: detecting singular dependencies between random variables

As part of the PrefStat summer school, Integreat organises 2nd International Summer School on Preference Learning at the University of Oslo. 

A one day workshop on Veridical Data Science (VDS) in Rome, is co-organized by Integreat, the Norwegian centre for knowledge-driven machine learning in Oslo, the Department of Statistics, University of California, Berkeley,  the L’EMbeDS Department of Excellence at the Sant’Anna School of Advanced Studies at Pisa, and the Department of Methods and Models for Economics, Territory and Finance of the University of Roma La Sapienza and the Institute for Systems Analysis and Computer Science of the Italian National Research Council.

Researchers and representatives from civil society seek to investigate the impact of generative AI in relation to justice and war crimes.

Systems that learn and reason