1 citations · 2 across the 23 of their papers we have counts for
6 papers · 1 filter
Towards modeling evolving longitudinal health trajectories with a transformer-based deep learning model
Hans Moen, Vishnu Raj, Andrius Vabalas +4
Health registers contain rich information about individuals' health histories. Here our interest lies in understanding how individuals' health trajectories evolve in a nationwide l…
Proxy-informed Bayesian transfer learning with unknown sources
Sabina J. Sloman, Julien Martinelli, Samuel Kaski
Generalization outside the scope of one's training data requires leveraging prior knowledge about the effects that transfer, and the effects that don't, between different data sour…
Identifying latent disease factors differently expressed in patient subgroups using group factor analysis
Fabio S. Ferreira, John Ashburner, Arabella Bouzigues +33
In this study, we propose a novel approach to uncover subgroup-specific and subgroup-common latent factors addressing the challenges posed by the heterogeneity of neurological and…
Amortized Probabilistic Conditioning for Optimization, Simulation and Inference
Paul E. Chang, Nasrulloh Loka, Daolang Huang +3
Amortized meta-learning methods based on pre-training have propelled fields like natural language processing and vision. Transformer-based neural processes and their variants are l…
Cost-aware simulation-based inference
Ayush Bharti, Daolang Huang, Samuel Kaski +1
Simulation-based inference (SBI) is the preferred framework for estimating parameters of intractable models in science and engineering. A significant challenge in this context is t…
Video-Language Critic: Transferable Reward Functions for Language-Conditioned Robotics
Minttu Alakuijala, Reginald McLean, Isaac Woungang +4
Natural language is often the easiest and most convenient modality for humans to specify tasks for robots. However, learning to ground language to behavior typically requires impra…