Sincerely thank you @miccaisociety.bsky.social for this huge honor. I am sure this will be very motivating for Ziyun and the lab to keep pushing forward. Thank you! 🫡 🥰 🤗
26.09.2025 13:25 — 👍 2 🔁 0 💬 0 📌 0
IterMask3D: Unsupervised anomaly detection and segmentation with test-time iterative mask refinement in 3D brain MRI
Unsupervised anomaly detection and segmentation methods train a model to learn the training distribution as ‘normal’. In the testing phase, they ident…
🤖 The paper introduces, IterMask3D, an unsupervised (no training labels) 3D model for detection & segmentation of unexpected artifacts (quality control/reliability) and brain lesions in brain MRI 🏥
😀So proud for the growth of our students. Thanks team for the hard work🫡
26.09.2025 13:20 — 👍 0 🔁 0 💬 0 📌 0
🥳🎊🥂 She won it! She won it! She won it! 🎉🎊🥂
🏆🏅Best Paper Award #MICCAI2025 for our #MedIA article!🏅🏆
One of most prestigious awards in #Medical #Imaging that I could only dream when starting a lab 3 years ago, but @ziyunliang.bsky.social made it!
📜 Paper: www.sciencedirect.com/science/arti...
🧵👇
26.09.2025 13:20 — 👍 4 🔁 0 💬 2 📌 0
Really proud of the lab's progress and the growth of our students: Decentralised Isolation Networks (DIsoN) for out-of-distribution detection accepted to #NeurIPS2025 !
20.09.2025 09:08 — 👍 3 🔁 0 💬 0 📌 0
📣 New article on MedIA, a fantastic job by Ziyun:
🤖🏥IterMask3D: Unsupervised Anomaly Detection and Segmentation in 3D Brain MRI
-AI that detects problematic image artifacts (eg Quality Control for reliability)
-Advances unsupervised lesion segmentation
-No labels for training
Open Access & code👇
19.09.2025 10:45 — 👍 2 🔁 0 💬 0 📌 0
Towards foundational models for Brain Lesion Segmentation with Multi-Modal MRI, vol.2 from our lab:
We show it s feasible to train 1 model with Federated Learning on clients with different brain lesions and MRI modalities, with performance similar to centralised.
Oral @wacvconference.bsky.social
27.01.2025 19:58 — 👍 4 🔁 0 💬 0 📌 0
Research at Google DeepMind. Ex-Physicist. Controllable World Simulators (GNNs, Structured World Models, Neural Assets). TLM Veo Capabilities (Ingredients & more).
📍 San Francisco, CA
Research Scientist at DeepMind. Opinions my own. Inventor of GANs. Lead author of http://www.deeplearningbook.org . Founding chairman of www.publichealthactionnetwork.org
Working towards the safe development of AI for the benefit of all at Université de Montréal, LawZero and Mila.
A.M. Turing Award Recipient and most-cited AI researcher.
https://lawzero.org/en
https://yoshuabengio.org/profile/
Researcher at Google and CIFAR Fellow, working on the intersection of machine learning and neuroscience in Montréal (academic affiliations: @mcgill.ca and @mila-quebec.bsky.social).
Director Data Science Institute @UWMadison, Professor of Physics,
EiC @MLSTjournal. Physics, stats/ML/AI, open science.
Founder & executive & community builder & organizer & researcher
ML Collective (mlcollective.org)
Google DeepMind
rosanneliu.com
Cofounded and lead PyTorch at Meta. Also dabble in robotics at NYU.
AI is delicious when it is accessible and open-source.
http://soumith.ch
AI + security | Stanford PhD in AI & Cambridge physics | techno-optimism + alignment + progress + growth | 🇺🇸🇨🇿
Señor swesearcher @ Google DeepMind, adjunct prof at Université de Montréal and Mila. Musician. From 🇪🇨 living in 🇨🇦.
https://psc-g.github.io/
Strengthening Europe's Leadership in AI through Research Excellence | ellis.eu
Official account for the IEEE/CVF International Conference on Computer Vision. #ICCV2025 Honolulu 🇺🇸 Co-hosted by @natanielruiz @antoninofurnari @yaelvinker @CSProfKGD
Official account for IEEE/CVF Conference on Computer Vision & Pattern Recognition. Hosted by @CSProfKGD with more to come.
📍🌎 🔗 cvpr.thecvf.com 🎂 June 19, 1983
AI for storytelling, games, explainability, safety, ethics. Professor at Georgia Tech. Associate Director of ML Center at GT. Time travel expert. Geek. Dad. he/him
Professor for Visual Computing & Artificial Intelligence @TU Munich
Co-Founder @synthesiaIO
Co-Founder @SpAItialAI
https://niessnerlab.org/publications.html
Professor of Computer Vision, @BristolUni. Senior Research Scientist @GoogleDeepMind - passionate about the temporal stream in our lives.
http://dimadamen.github.io
Associate Professor in Machine Learning at the University of Oxford.
Interested in automatic inductive bias selection using Bayesian tools.
International Conference on Learning Representations https://iclr.cc/
Research Director, Founding Faculty, Canada CIFAR AI Chair @VectorInst.
Full Prof @UofT - Statistics and Computer Sci. (x-appt) danroy.org
I study assumption-free prediction and decision making under uncertainty, with inference emerging from optimality.
Assistant Professor, University of Toronto.
Junior Research Fellow, Trinity College, Cambridge.
AI Fellow, Georgetown University.
Probabilistic Machine Learning, AI Safety & AI Governance.
Prev: Oxford, Yale, UC Berkeley, NYU.
https://timrudner.com
