12 citations · 13 across the 5 of their papers we have counts for
6 papers
SwInception -- Local Attention Meets Convolutions
David Hagerman, Roman Naeem, Jakob Lindqvist +3
Sparse vision transformers have gained popularity as efficient encoders for medical volumetric segmentation, with Swin emerging as a prominent choice. Swin uses local attention to…
On the connection between Noise-Contrastive Estimation and Contrastive Divergence
Amanda Olmin, Jakob Lindqvist, Lennart Svensson +1
Noise-contrastive estimation (NCE) is a popular method for estimating unnormalised probabilistic models, such as energy-based models, which are effective for modelling complex data…
MCMC-Correction of Score-Based Diffusion Models for Model Composition
Anders Sjöberg, Jakob Lindqvist, Magnus Önnheim +2
Diffusion models can be parameterized in terms of either score or energy function. The energy parameterization is attractive as it enables sampling procedures such as Markov Chain…
Active Learning with Weak Supervision for Gaussian Processes
Amanda Olmin, Jakob Lindqvist, Lennart Svensson +1
Annotating data for supervised learning can be costly. When the annotation budget is limited, active learning can be used to select and annotate those observations that are likely…
Posterior linearisation smoothing with robust iterations
Jakob Lindqvist, Simo Särkkä, Ángel F. García-Fernández +2
This paper considers the problem of iterative Bayesian smoothing in nonlinear state-space models with additive noise using Gaussian approximations. Iterative methods are known to i…
A general framework for ensemble distribution distillation
Jakob Lindqvist, Amanda Olmin, Fredrik Lindsten +1
Ensembles of neural networks have been shown to give better performance than single networks, both in terms of predictions and uncertainty estimation. Additionally, ensembles allow…