22 citations · 28 across the 7 of their papers we have counts for
7 papers
Asymptotically Exact and Fast Gaussian Copula Models for Imputation of Mixed Data Types
Benjamin Christoffersen, Mark Clements, Keith Humphreys +1
Missing values with mixed data types is a common problem in a large number of machine learning applications such as processing of surveys and in different medical applications. Rec…
Full-Glow: Fully conditional Glow for more realistic image generation
Moein Sorkhei, Gustav Eje Henter, Hedvig Kjellström
Autonomous agents, such as driverless cars, require large amounts of labeled visual data for their training. A viable approach for acquiring such data is training a generative mode…
Action Graphs: Weakly-supervised Action Localization with Graph Convolution Networks
Maheen Rashid, Hedvig Kjellström, Yong Jae Lee
We present a method for weakly-supervised action localization based on graph convolutions. In order to find and classify video time segments that correspond to relevant action clas…
A Hierarchical Grocery Store Image Dataset with Visual and Semantic Labels
Marcus Klasson, Cheng Zhang, Hedvig Kjellström
Image classification models built into visual support systems and other assistive devices need to provide accurate predictions about their environment. We focus on an application o…
Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation
Charles Hamesse, Ruibo Tu, Paul Ackermann +2
Achilles Tendon Rupture (ATR) is one of the typical soft tissue injuries. Rehabilitation after such a musculoskeletal injury remains a prolonged process with a very variable outcom…
Causal Discovery in the Presence of Missing Data
Ruibo Tu, Kun Zhang, Paul Ackermann +4
Missing data are ubiquitous in many domains including healthcare. When these data entries are not missing completely at random, the (conditional) independence relations in the obse…
Factorized Topic Models
Cheng Zhang, Carl Henrik Ek, Andreas Damianou +1
In this paper we present a modification to a latent topic model, which makes the model exploit supervision to produce a factorized representation of the observed data. The structur…