39 citations · 41 across the 6 of their papers we have counts for
6 papers
Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection
Pramit Saha, Divyanshu Mishra, Felix Wagner +2
Multimodal Federated Learning (MMFL) utilizes multiple modalities in each client to build a more powerful Federated Learning (FL) model than its unimodal counterpart. However, the…
Light Dark Matter Search Using a Diamond Cryogenic Detector
CRESST Collaboration, G. Angloher, S. Banik +56
Diamond operated as a cryogenic calorimeter is an excellent target for direct detection of low-mass dark matter candidates. Following the realization of the first low-threshold cry…
Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment
Felix Wagner, Zeju Li, Pramit Saha +1
Deployment of Deep Neural Networks in medical imaging is hindered by distribution shift between training data and data processed after deployment, causing performance degradation.…
Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI
Ziyun Liang, Harry Anthony, Felix Wagner +1
Unsupervised anomaly segmentation aims to detect patterns that are distinct from any patterns processed during training, commonly called abnormal or out-of-distribution patterns, w…
Testing spin-dependent dark matter interactions with lithium aluminate targets in CRESST-III
G. Angloher, S. Banik, G. Benato +58
In the past decades, numerous experiments have emerged to unveil the nature of dark matter, one of the most discussed open questions in modern particle physics. Among them, the CRE…
Nonlinear pile-up separation with LSTM neural networks for cryogenic particle detectors
Felix Wagner
In high-background or calibration measurements with cryogenic particle detectors, a significant share of the exposure is lost due to pile-up of recoil events. We propose a method f…