activity
20222024
most citedCellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations

3 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.BM2024★ 2 cited

BetterBodies: Reinforcement Learning guided Diffusion for Antibody Sequence Design

Yannick Vogt, Mehdi Naouar, Maria Kalweit +4

Antibodies offer great potential for the treatment of various diseases. However, the discovery of therapeutic antibodies through traditional wet lab methods is expensive and time-c…

q-bio.BM2024★ 2 cited

Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design

Yannick Vogt, Mehdi Naouar, Maria Kalweit +5

The field of antibody-based therapeutics has grown significantly in recent years, with targeted antibodies emerging as a potentially effective approach to personalized therapies. S…

cs.CV2023★ 3 cited

CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations

Mehdi Naouar, Gabriel Kalweit, Anusha Klett +6

In recent years, several unsupervised cell segmentation methods have been presented, trying to omit the requirement of laborious pixel-level annotations for the training of a cell…

cs.CV2023★ 2 cited

Robust Tumor Detection from Coarse Annotations via Multi-Magnification Ensembles

Mehdi Naouar, Gabriel Kalweit, Ignacio Mastroleo +4

Cancer detection and classification from gigapixel whole slide images of stained tissue specimens has recently experienced enormous progress in computational histopathology. The li…

cs.CV2022

Probing Contextual Diversity for Dense Out-of-Distribution Detection

Silvio Galesso, Maria Alejandra Bravo, Mehdi Naouar +1

Detection of out-of-distribution (OoD) samples in the context of image classification has recently become an area of interest and active study, along with the topic of uncertainty…