Detailed Program

This workshop will be a full day event on October 3rd, 2023 in room E07.

Program (all times in CEST):

09:00 – 09:40 (40min) – Anna Kreshuk (invited speaker): Microscopy image segmentation with little training data

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09:40 – 10:20 (40min) – Flash talks

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10:20 – 10:40 (20min) – Coffee break

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10:40 – 11:20 (40min) – Flash talks

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11:20 – 11:40 (20min)Josef Lorenz Rumberger: ACTIS: Improving data efficiency by leveraging semi-supervised Augmentation Consistency Training for Instance Segmentation

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11:40 – 12:00 (20min)Jan Oscar Cross-Zamirski: Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels

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12:00 – 13:00 (60min) – Lunch break

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13:00 – 13:20 (20min)Benjamin Salmon: Direct Unsupervised Denoising

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13:20 – 13:40 (20min) – Josef Cersovsky: Towards Hierarchical Regional Transformer-based Multiple Instance Learning

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13:40 – 14:20 (40min) – Srinivas Turaga (invited speaker): Programmable microscopy enabled by differentiable optical simulation and FourierNets

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14:20 – 14:40 (20min) – Dig Vijay Kumar Yarlagadda: Discrete Representation Learning for Modeling Imaging-based Spatial Transcriptomics Data

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14:40 – 15:00 (20min) – Christopher Joseph Soelistyo: Virtual perturbations to assess explainability of deep-learning based cell fate predictors

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15:00 – 16:00 (60min) – Poster Session

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16:00 – 16:40 (40min) – Rene Vidal (invited speaker): Machine Learning in Hematology: Reinventing the Blood Test

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16:40 – 17:20 (40min)Shreya Saxena (invited speaker): Building in anatomical constraints to better understand functional imaging data.

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17:20 – 18:00 (40min) – Emma Lundberg (invited speaker): From image-based mapping to modeling of human cells


Previous editions...