21 citations · 85 across the 15 of their papers we have counts for
15 papers
ASMR: Angular Support for Malfunctioning Client Resilience in Federated Learning
Mirko Konstantin, Moritz Fuchs, Anirban Mukhopadhyay
Federated Learning (FL) allows the training of deep neural networks in a distributed and privacy-preserving manner. However, this concept suffers from malfunctioning updates sent b…
Regulating radiology AI medical devices that evolve in their lifecycle
Camila González, Moritz Fuchs, Daniel Pinto dos Santos +9
Over time, the distribution of medical image data drifts due to factors such as shifts in patient demographics, acquisition devices, and disease manifestations. While human radiolo…
GAUDA: Generative Adaptive Uncertainty-guided Diffusion-based Augmentation for Surgical Segmentation
Yannik Frisch, Christina Bornberg, Moritz Fuchs +1
Augmentation by generative modelling yields a promising alternative to the accumulation of surgical data, where ethical, organisational and regulatory aspects must be considered. Y…
Federated-Continual Dynamic Segmentation of Histopathology guided by Barlow Continuity
Niklas Babendererde, Haozhe Zhu, Moritz Fuchs +2
Federated- and Continual Learning have been established as approaches to enable privacy-aware learning on continuously changing data, as required for deploying AI systems in histop…
From Pointwise to Powerhouse: Initialising Neural Networks with Generative Models
Christian Harder, Moritz Fuchs, Yuri Tolkach +1
Traditional initialisation methods, e.g. He and Xavier, have been effective in avoiding the problem of vanishing or exploding gradients in neural networks. However, they only use s…
Exploring SAM Ablations for Enhancing Medical Segmentation in Radiology and Pathology
Amin Ranem, Niklas Babendererde, Moritz Fuchs +1
Medical imaging plays a critical role in the diagnosis and treatment planning of various medical conditions, with radiology and pathology heavily reliant on precise image segmentat…
Jointly Exploring Client Drift and Catastrophic Forgetting in Dynamic Learning
Niklas Babendererde, Moritz Fuchs, Camila Gonzalez +2
Federated and Continual Learning have emerged as potential paradigms for the robust and privacy-aware use of Deep Learning in dynamic environments. However, Client Drift and Catast…
Synthesising Rare Cataract Surgery Samples with Guided Diffusion Models
Yannik Frisch, Moritz Fuchs, Antoine Sanner +7
Cataract surgery is a frequently performed procedure that demands automation and advanced assistance systems. However, gathering and annotating data for training such systems is re…
Federated Stain Normalization for Computational Pathology
Nicolas Wagner, Moritz Fuchs, Yuri Tolkach +1
Although deep federated learning has received much attention in recent years, progress has been made mainly in the context of natural images and barely for computational pathology.…
Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation
Camila Gonzalez, Karol Gotkowski, Moritz Fuchs +5
Automatic segmentation of ground glass opacities and consolidations in chest computer tomography (CT) scans can potentially ease the burden of radiologists during times of high res…
FrOoDo: Framework for Out-of-Distribution Detection
Jonathan Stieber, Moritz Fuchs, Anirban Mukhopadhyay
FrOoDo is an easy-to-use and flexible framework for Out-of-Distribution detection tasks in digital pathology. It can be used with PyTorch classification and segmentation models, an…
Equilibration in closed quantum systems: Application to spin qubits
Daniel Hetterich, Moritz Fuchs, Björn Trauzettel
We study an observable-based notion of equilibration and its application to realistic systems like spin qubits in quantum dots. On the basis of the so-called distinguishability, we…
Thermal electron spin flip in quantum dots
Moritz Fuchs, Felix Krauß, Daniel Hetterich +1
We study a thermally induced spin flip of an electron spin located in a semiconductor quantum dot. This interesting effect arises from an intriguing interplay between the Zeeman co…
Ultra long spin decoherence times in graphene quantum dots with a small number of nuclear spins
Moritz Fuchs, John Schliemann, Björn Trauzettel
We study the dynamics of an electron spin in a graphene quantum dot, which is interacting with a bath of less than ten nuclear spins via the anisotropic hyperfine interaction. Due…
Spin decoherence in graphene quantum dots due to hyperfine interaction
Moritz Fuchs, Valentin Rychkov, Björn Trauzettel
Carbon based systems are prominent candidates for a solid-state spin-qubit due to weak spin-orbit and hyperfine interactions in combination with a low natural abundance of spin car…