2 citations · 3 across the 8 of their papers we have counts for
9 papers
Learning Functional Subspaces for Neural Network Compression
Massimo Bini, Anders Christensen, Stephan Alaniz +5
Modern transformers pair impressive capabilities with substantial memory and compute demands. Low-rank weight factorization reduces both while keeping the matrices dense, and thus…
Explaining CLIP Zero-shot Predictions Through Concepts
Onat Ozdemir, Anders Christensen, Stephan Alaniz +2
Large-scale vision-language models such as CLIP have achieved remarkable success in zero-shot image recognition, yet their predictions remain largely opaque to human understanding.…
Geometry Fidelity for Spherical Images
Anders Christensen, Nooshin Mojab, Khushman Patel +5
Spherical or omni-directional images offer an immersive visual format appealing to a wide range of computer vision applications. However, geometric properties of spherical images p…
DiffEnc: Variational Diffusion with a Learned Encoder
Beatrix M. G. Nielsen, Anders Christensen, Andrea Dittadi +1
Diffusion models may be viewed as hierarchical variational autoencoders (VAEs) with two improvements: parameter sharing for the conditional distributions in the generative process…
Image-free Classifier Injection for Zero-Shot Classification
Anders Christensen, Massimiliano Mancini, A. Sophia Koepke +2
Zero-shot learning models achieve remarkable results on image classification for samples from classes that were not seen during training. However, such models must be trained from…
Addressing caveats of neural persistence with deep graph persistence
Leander Girrbach, Anders Christensen, Ole Winther +2
Neural Persistence is a prominent measure for quantifying neural network complexity, proposed in the emerging field of topological data analysis in deep learning. In this work, how…
Removing confounding information from fetal ultrasound images
Kamil Mikolaj, Manxi Lin, Zahra Bashir +4
Confounding information in the form of text or markings embedded in medical images can severely affect the training of diagnostic deep learning algorithms. However, data collected…
Incorporating High-Frequency Weather Data into Consumption Expenditure Predictions
Anders Christensen, Joel Ferguson, Simón Ramírez Amaya
Recent efforts have been very successful in accurately mapping welfare in datasparse regions of the world using satellite imagery and other non-traditional data sources. However, t…
Optimal Variance Control of the Score Function Gradient Estimator for Importance Weighted Bounds
Valentin Liévin, Andrea Dittadi, Anders Christensen +1
This paper introduces novel results for the score function gradient estimator of the importance weighted variational bound (IWAE). We prove that in the limit of large (number o…