8.1k citations · 11.5k across the 25 of their papers we have counts for
17 papers · 1 filter
DNA: Differentially private Neural Augmentation for contact tracing
Rob Romijnders, Christos Louizos, Yuki M. Asano +1
The COVID19 pandemic had enormous economic and societal consequences. Contact tracing is an effective way to reduce infection rates by detecting potential virus carriers early. How…
Binding Dynamics in Rotating Features
Sindy Löwe, Francesco Locatello, Max Welling
In human cognition, the binding problem describes the open question of how the brain flexibly integrates diverse information into cohesive object representations. Analogously, in m…
Lie Point Symmetry and Physics Informed Networks
Tara Akhound-Sadegh, Laurence Perreault-Levasseur, Johannes Brandstetter +2
Symmetries have been leveraged to improve the generalization of neural networks through different mechanisms from data augmentation to equivariant architectures. However, despite t…
Flow Factorized Representation Learning
Yue Song, T. Anderson Keller, Nicu Sebe +1
A prominent goal of representation learning research is to achieve representations which are factorized in a useful manner with respect to the ground truth factors of variation. Th…
Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes
Tim Bakker, Herke van Hoof, Max Welling
Pool-based active learning (AL) is a promising technology for increasing data-efficiency of machine learning models. However, surveys show that performance of recent AL methods is…
Efficient Neural PDE-Solvers using Quantization Aware Training
Winfried van den Dool, Tijmen Blankevoort, Max Welling +1
In the past years, the application of neural networks as an alternative to classical numerical methods to solve Partial Differential Equations has emerged as a potential paradigm s…