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...