1 citations · 3 across the 7 of their papers we have counts for
7 papers
Space-Time Continuous PDE Forecasting using Equivariant Neural Fields
David M. Knigge, David R. Wessels, Riccardo Valperga +4
Recently, Conditional Neural Fields (NeFs) have emerged as a powerful modelling paradigm for PDEs, by learning solutions as flows in the latent space of the Conditional NeF. Althou…
Grounding Continuous Representations in Geometry: Equivariant Neural Fields
David R Wessels, David M Knigge, Samuele Papa +4
Conditional Neural Fields (CNFs) are increasingly being leveraged as continuous signal representations, by associating each data-sample with a latent variable that conditions a sha…
How to Train Neural Field Representations: A Comprehensive Study and Benchmark
Samuele Papa, Riccardo Valperga, David Knigge +4
Neural fields (NeFs) have recently emerged as a versatile method for modeling signals of various modalities, including images, shapes, and scenes. Subsequently, a number of works h…
Data Augmentations in Deep Weight Spaces
Aviv Shamsian, David W. Zhang, Aviv Navon +10
Learning in weight spaces, where neural networks process the weights of other deep neural networks, has emerged as a promising research direction with applications in various field…
Neural Modulation Fields for Conditional Cone Beam Neural Tomography
Samuele Papa, David M. Knigge, Riccardo Valperga +4
Conventional Computed Tomography (CT) methods require large numbers of noise-free projections for accurate density reconstructions, limiting their applicability to the more complex…
Learning Lie Group Symmetry Transformations with Neural Networks
Alex Gabel, Victoria Klein, Riccardo Valperga +4
The problem of detecting and quantifying the presence of symmetries in datasets is useful for model selection, generative modeling, and data analysis, amongst others. While existin…
Learning reversible symplectic dynamics
Riccardo Valperga, Kevin Webster, Victoria Klein +2
Time-reversal symmetry arises naturally as a structural property in many dynamical systems of interest. While the importance of hard-wiring symmetry is increasingly recognized in m…