University of Oslo and University of Gothenburg invite to an informal workshop within machine learning with a focus on statistical aspects related to Machine Learning.
About
Researchers within statistics from University of Oslo and University of Gothenburg gather to present and discuss their work with fellow researchers.
This workshop is by invitation. Contact Geir Storvik (geirs@math.uio.no) for those at UiO or Rebecka Jörnsten (jornsten@chalmers.se) for those from Gothenburg if you have not received an invitation, but would like to attend. Conference fee is 4000 NOK, covering accommodation (1 night) and all meals at the workshop.
Program (there might be small changes)
Monday 18 March
| 11:00 - 11:10 | Welcome, Geir Storvik |
|---|---|
| 11:10-11.45 | Integreat - Norwegian Centre for Knowledge-driven Machine Learning (Arnoldo Frigessi, UiO) |
| 11.45:12:30 | ML, AI and Statistics: challenges and opportunties for research and teaching (Rebecka Jörnsten, Chalmers) |
| 12:30 - 13:30 | Lunch |
| 13:30 - 15:00 | Towards Data-Conditional Simulation for ABC Inference in Stochastic Differential Equations (Peter Jovanovski, Chalmers) Sequential simulation-based inference using Gaussian locally linear mappings (Henrik Häggström, Chalmers) Synthetic data with vine copulas – balancing utility and privacy (Ingrid Hobæk Haff, UiO) |
| 15:00 - 15:15 | BREAK |
| 15:15 - 16:30 |
Evaluation of extreme forecasts (Thordis Thorarinsdottir, UiO) Discussion session: How to promote further collaboration? |
| 19:00 - 21:00 | DINNER |
Tuesday 19 March
| 8:00 - 9:00 | BREAKFAST |
|---|---|
| 9:00 - 10:30 | Causality and Machine Learning (Johan Pensar, UiO) Targeted minimum loss estimation to recover causal parameters (J. de Aquas, UiO) Bayesian estimation of causal effects from observational categorical data (V. Kvisgaard, UiO) |
| 10:30-10:45 | BREAK |
| 10:45-11:30 | Bayesian Neural Networks in the Age of Large-Scale Deep Learning (Aliaksandr Hubin, NMBU) |
| 11:30-12:00 | Introducing skip connections in Bayesian Neural Networks for more interpretable models (E. Høyheim, NMBU)
|
| 12:00 - 13:00 | LUNCH |
| 13:00 - 14:30 | Bayesian Generalised Nonlinear Models: Inference, Software, and Applications (Geir Storvik, UiO) Emergence of Equivariance in Deep Ensembles (Jan Gerken, Chalmers) Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration (Ziming Wang, Chalmers) |
| 14:30 - 14:45 | BREAK |
| 15:00-15:45 | Summary of discussion |
| 15:45-16.00 | End |