2 code implementations • 4 Dec 2020 • Nicolas Wagner, Anirban Mukhopadhyay
Super-Selfish is an easy to use PyTorch framework for image-based self-supervised learning.
1 code implementation • 29 Sep 2022 • Nicolas Wagner, Moritz Fuchs, Yuri Tolkach, Anirban Mukhopadhyay
As a solution, we propose BottleGAN, a generative model that can computationally align the staining styles of many laboratories and can be trained in a privacy-preserving manner to foster federated learning in computational pathology.
1 code implementation • 7 Dec 2021 • Marius Memmel, Christoph Reich, Nicolas Wagner, Faraz Saeedan
With the increased availability of 3D data, the need for solutions processing those also increased rapidly.
1 code implementation • 15 Apr 2024 • Nicolas Wagner, Dongyang Fan, Martin Jaggi
We explore on-device self-supervised collaborative fine-tuning of large language models with limited local data availability.
no code implementations • JEPTALNRECITAL 2018 • Nicolas Wagner, Romaric Besan{\c{c}}on, Olivier Ferret
L{'}identification des entit{\'e}s nomm{\'e}es dans un texte est une {\'e}tape fondamentale pour de nombreuses t{\^a}ches d{'}extraction d{'}information.
no code implementations • 15 Dec 2020 • Sophie Burkhardt, Jannis Brugger, Nicolas Wagner, Zahra Ahmadi, Kristian Kersting, Stefan Kramer
Most deep neural networks are considered to be black boxes, meaning their output is hard to interpret.
no code implementations • 15 Dec 2020 • Nicolas Wagner, Ulrich Schwanecke
As evaluating the EMD on high resolution point clouds is intractable, we propose a divide-and-conquer approach based on k-d trees, the EM-kD, as a scaleable and fast but still reliable upper bound for the EMD.
no code implementations • LREC 2022 • Matthias Kraus, Nicolas Wagner, Wolfgang Minker
For creating a sound interactive personalization, we have developed an empathy-augmented dialogue strategy.
no code implementations • 25 Nov 2022 • Matthias Kraus, Nicolas Wagner, Ron Riekenbrauck, Wolfgang Minker
The next step for intelligent dialog agents is to escape their role as silent bystanders and become proactive.