7 papers
Proper Scoring Rules for Right-Censored Survival Data
Jef Jonkers, Glenn Van Wallendael, Luc Duchateau +1
Proper scoring rules provide a rigorous theoretical basis for the training and evaluation of probabilistic forecasts. However, in the presence of right censoring, the event time is…
TGIF2: Extended Text-Guided Inpainting Forgery Dataset & Benchmark
Hannes Mareen, Dimitrios Karageorgiou, Paschalis Giakoumoglou +3
Generative AI has made text-guided inpainting a powerful image editing tool, but at the same time a growing challenge for media forensics. Existing benchmarks, including our text-g…
Generative Anchored Fields: Controlled Data Generation via Emergent Velocity Fields and Transport Algebra
Deressa Wodajo Deressa, Hannes Mareen, Peter Lambert +1
We present Generative Anchored Fields (GAF), a generative model that learns independent endpoint predictors, (noise) and (data), from any point on a linear bridge. Unlike e…
POTR: Post-Training 3DGS Compression
Bert Ramlot, Martijn Courteaux, Peter Lambert +1
3D Gaussian Splatting (3DGS) has recently emerged as a promising contender to Neural Radiance Fields (NeRF) in 3D scene reconstruction and real-time novel view synthesis. 3DGS outp…
Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects
Jef Jonkers, Jarne Verhaeghe, Glenn Van Wallendael +2
Generating probabilistic forecasts of potential outcomes and individual treatment effects (ITE) is essential for risk-aware decision-making in domains such as healthcare, policy, m…
landmarker: a Toolkit for Anatomical Landmark Localization in 2D/3D Images
Jef Jonkers, Luc Duchateau, Glenn Van Wallendael +1
Anatomical landmark localization in 2D/3D images is a critical task in medical imaging. Although many general-purpose tools exist for landmark localization in classical computer vi…