15.1k citations · 36.9k across the 152 of their papers we have counts for
21 papers · 1 filter
Quantum Deformed Neural Networks
Roberto Bondesan, Max Welling
We develop a new quantum neural network layer designed to run efficiently on a quantum computer but that can be simulated on a classical computer when restricted in the way it enta…
Self Normalizing Flows
T. Anderson Keller, Jorn W. T. Peters, Priyank Jaini +3
Efficient gradient computation of the Jacobian determinant term is a core problem in many machine learning settings, and especially so in the normalizing flow framework. Most propo…
Probabilistic Numeric Convolutional Neural Networks
Marc Finzi, Roberto Bondesan, Max Welling
Continuous input signals like images and time series that are irregularly sampled or have missing values are challenging for existing deep learning methods. Coherently defined feat…
Experimental design for MRI by greedy policy search
Tim Bakker, Herke van Hoof, Max Welling
In today's clinical practice, magnetic resonance imaging (MRI) is routinely accelerated through subsampling of the associated Fourier domain. Currently, the construction of these s…
Orbital MCMC
Kirill Neklyudov, Max Welling
Markov Chain Monte Carlo (MCMC) algorithms ubiquitously employ complex deterministic transformations to generate proposal points that are then filtered by the Metropolis-Hastings-G…
Federated Learning of User Authentication Models
Hossein Hosseini, Sungrack Yun, Hyunsin Park +3
Machine learning-based User Authentication (UA) models have been widely deployed in smart devices. UA models are trained to map input data of different users to highly separable em…