1 code implementation • 30 Jan 2019 • Sebastian Mathias Keller, Maxim Samarin, Mario Wieser, Volker Roth
"Deep Archetypal Analysis" generates latent representations of high-dimensional datasets in terms of fractions of intuitively understandable basic entities called archetypes.
1 code implementation • 3 Feb 2020 • Sebastian Mathias Keller, Maxim Samarin, Fabricio Arend Torres, Mario Wieser, Volker Roth
The real-world applicability of the proposed method is demonstrated by exploring archetypes of female facial expressions while using multi-rater based emotion scores of these expressions as side information.
no code implementations • 24 Jun 2020 • Maxim Samarin, Volker Roth, David Belius
The Neural Tangent Kernel (NTK) is an important milestone in the ongoing effort to build a theory for deep learning.
1 code implementation • 25 Nov 2021 • Maxim Samarin, Vitali Nesterov, Mario Wieser, Aleksander Wieczorek, Sonali Parbhoo, Volker Roth
We address these shortcomings with a novel approach to cycle consistency.
no code implementations • 14 Apr 2022 • Vitali Nesterov, Fabricio Arend Torres, Monika Nagy-Huber, Maxim Samarin, Volker Roth
These networks represent functions that are guaranteed to have connected level sets forming smooth manifolds on the input space.
no code implementations • 3 Jun 2022 • Fabricio Arend Torres, Marcello Massimo Negri, Monika Nagy-Huber, Maxim Samarin, Volker Roth
Physics-informed Neural Networks (PINNs) have recently emerged as a principled way to include prior physical knowledge in form of partial differential equations (PDEs) into neural networks.