47 citations · 171 across the 19 of their papers we have counts for
4 papers · 1 filter
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…
PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers
Phillip Lippe, Bastiaan S. Veeling, Paris Perdikaris +2
Time-dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniqu…
BISCUIT: Causal Representation Learning from Binary Interactions
Phillip Lippe, Sara Magliacane, Sindy Löwe +3
Identifying the causal variables of an environment and how to intervene on them is of core value in applications such as robotics and embodied AI. While an agent can commonly inter…
Rotating Features for Object Discovery
Sindy Löwe, Phillip Lippe, Francesco Locatello +1
The binding problem in human cognition, concerning how the brain represents and connects objects within a fixed network of neural connections, remains a subject of intense debate.…