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The latest paper from the BloodCounts! consortium has been published in Patterns, a Cell Press journal 🔔📢 A methodological review of federated learning for healthcare is available here doi.org/10.1016/j.patt… Carola-Bibiane Schönlieb James Rudd John Aston @srndittmer nick gleadall tolou shadbahr

Today's seminar featured Simon Deltadahl from BloodCounts! presenting a novel diffusion-based approach for blood cell classification! @THaavardsholm from Universitetet i Oslo shared insights on situational awareness for autonomous platforms. Inspiring discussions! 🌟

We had an exciting CIA Group seminar today! 🎉 Huge thanks to Carola-Bibiane Schönlieb for her talk on "From Geometric PDEs and Variational Modelling to Deep Learning for Images" and Maya Bechler-Speicher from Tel Aviv University on "Mitigating Graph Overfitting in GNNs". #Innovation

In today’s CIA seminar, we were thrilled to welcome Christina Runkel for an insightful talk on Reconstructing Training Data🤖. Huge thanks also to Erik Jansson from Göteborgs universitet / University of Gothenburg, who shared his research on Geometric Shape Matching for Single-Particle Cryo-EM Data🧬🔬. #AI

📣 Registration to the NeurIPS meetup@Cambridge on Fri 6 Dec is now open! If you would like to discuss the ML research being presented at #Neurips2024 register here: buff.ly/3CpXQWw. Further details of the event can be found on the website: buff.ly/3YZFzbj

Today's CIA seminar was packed with insights! 🎓✨ 🔹 Chriselda Oliver presented her insightful work on Laplace Learning in Wasserstein Space. 🔹 Wallace Peaslee shared fascinating work on Registering Archival Photos of Panel Paintings. #MachineLearning #ImageProcessing

Dr Anna Breger, working with Professor Carola Schönlieb Carola-Bibiane Schönlieb at the Cambridge Image Analysis group group in Faculty of Mathematics - University of Cambridge, will lead a project looking at imaging & ML methods for reconstructing degraded historical sheet music.

Fantastic talk from Zakhar Shumaylov at today's CIA seminar! 🚀 He shared insightful work on the Future of Synthetic Data, covering Model Collapse & Equivariant Neural Operators. 🔥 #AI #MachineLearning #SyntheticData

🚀 In today's CIA seminar, Daniel Kreuter shared insights on detecting iron deficiency in blood donors using full blood count data, while James Rowbottom introduced G-Adaptivity: an optimised graph-based mesh relocation technique for the finite element method. Fascinating talks!

I recently learned about a very cool fact: if you compose flows of two Hamiltonians, this is also Hamiltonian. What is more - you can write down the exact Hamiltonian!

🚀In today’s CIA seminar, we were delighted to have ander biguri discuss inverse problems, their role in CT/PET imaging, and the latest PET advancements. Kelly Kokka also shared insights on using computer vision to extract environmental characteristics from imagery. Great talks!

We had an exciting CIA seminar this week! Chriselda Oliver presented the Linear Wasserstein Framework, and Wallace Peaslee shared fascinating insights on degraded music manuscripts and potential contrast. Great discussions all around! #MusicRestoration #Wasserstein

In today's seminar, we were thrilled by Julian Gilbey's presentation on Validation Data Overuse & Translation into Practice. Insightful discussions and key takeaways on ensuring robust model evaluation! 🚀 #AI #MachineLearning #ModelValidation"

🩸📝 The BloodCounts! and Flower Labs are delighted to announce the first results of their year-long collaboration today! This collaboration brings together the largest global network of Full Blood Count (FBC) test data and research. Together with Fan Zhang, ML Scientist and

In SIAM News Online, Angelica Angelica I Aviles-Rivero and Carola-Bibiane Schönlieb (Carola-Bibiane Schönlieb) describe semi-supervised hybrid modeling in #healthcare, which preserves theoretical guarantees while achieving higher performance than pure #deeplearning models. siam.org/publications/s…

🚀 In today's CIA seminar, Leonardo Del Grande (University of Twente) shared valuable insights on Exact Sparse Representation Recovery in convex optimization. A fascinating deep dive into the power of sparsity! 💡🔍 #Optimization #SparseRecovery #MachineLearning

If you are coming to #ICLR2025 come say hello. We will be presenting on how to turn Neural Operators equivariant even when all you know is the lie algebra! Generally happy to chat all things #geometry and #optimization in deep learning! 🔗arxiv.org/pdf/2410.02698

🔬Exciting Friday seminar! Fan Zhang presented his production-ready Federated Learning platform for healthcare applications, while Zhongying Deng shared insights on Bilevel Hypergraph Networks for Multi-Modal Alzheimer's Diagnosis. Two fantastic talks advancing #HealthcareAI

We were delighted to have guest speaker Xue-Cheng Tai from NORCE present his research on PottsMGNet: A Mathematical Explanation of Encoder-Decoder Based Neural Networks. Fascinating insights into the theoretical foundations of #DeepLearning architectures! 🔍 #AIResearch

🎉 Congrats to Yichen Chen — Runner-up for Most Impactful Poster at UoC-AZ PhD Symposium! 🏅 "Automated Discovery of Real & Interpretable Image Biomarkers" And to Simon Deltadahl — CSAR PhD Award 2025 for "Deep Generative Classification of Blood Cell Morphology" 👏