Dear @icmlconf, our recent submission received overwhelmingly positive reviews yet was rejected based on the AC’s factually incorrect evaluation, ignoring all reviews and rebuttal. We reached out via email to no avail. What recourse do authors have in such situations? #ICML2025.

[Please share!] We are offering 2x full PhD scholarships in AI/ML for cardiovascular research. These are EPSRC-funded, 4-year scholarships reserved to candidates with Home/UK status. Reach out if interested! For more info: .

Paper & code for our unsupervised anomaly detection technique: Paper & code for our FETS entry: coming up, stay tuned! (2/2).

Great times at #MICCAI2024 in Marrakech! . See Vasilis Siomos, PhD candidate at @Cit_AI1, doing a great job at presenting our work on Unsupervised Anomaly Detection via cold diffusion (accepted at the main conf) and our entry to the FETS challenge on Federated Learning (1/2)

Code repo linked in the pre-print above. If interested, please feel free to reach out, either online or in person at MICCAI. Thanks to all our co-authors: Vasilis Siomos, @MertBTwit, @ctzelepis, @BernhardKainz1. #AI #medicalimaging #unsupervisedlearning.

DISYRE v2 outperforms all competitors in our experiments, and achieves +10% DICE over v1 on BraTS-T1 brain MR images! . See here some examples of test images, "healed" restorations and ensembled anomaly scores (grayscale) vs ground truth (red outline).

With v2, we expand on this work showing how 1) disentangling attributes of the generated anomalies during training and 2) ensembling predictions generated by varying the assumed anomaly severity at testing are key to substantially improve performance.

With DISYRE (, we showed how diffusion-like models can be trained replacing Gaussian noise with synthetic anomalies, setting a new state-of-the-art for unsupervised anomaly detection (i.e., training using only images of normal subjects).

Pushing unsupervised anomaly detection to greater heights!. Very happy to announce that our latest paper in the field, DISYRE v2, has been accepted for publication at #MICCAI2024. Pre-print: Work led by Sergio Naval Marimont @snavalm @Cit_AI1. 1/N:

The upcoming merger between St George's and City, University of London will create a new Medical School and open up many interesting opportunities. In particular, the appointed lecturer will work in collaboration with the CitAI Research Centre @Cit_AI1 (and yours truly).

Sharing an opening for a Senior Lecturer in AI at the Cardiovascular and Genomics Research Institute at @StGeorgesU (merging with @CityUniLondon this August). If you have a background in AI/ML for medical/cardiac data, apply!. More info: Please share!.

Looking for a #PhD student to work on Weakly-Supervised Machine Learning for Medical Image Analysis at @CityUniLondon and @StGeorgesUni! Competitive bursary, fees fully covered for Home students (partial coverage for Overseas ones). Please share!.

Please come and say hi if you'll be there. Congratulations to all co-authors!. Pre-prints:.ARIA: DISYRE:

Very excited that both DISYRE (Diffusion-Inspired SYnthetic REstoration for Unsupervised Anomaly Detection) and ARIA (Interaction between Architectures, Aggregation methods and Initializations in federated visual classification) have been accepted for presentation at ISBI 2024!.

Scholarship co-funded by @CityUniLondon and @CosmoIMD, global leaders in #AI for #medical #imaging with ground-breaking FDA-approved AI tools for medical video analysis. The candidate will join the @Cit_AI1 research centre under my supervision. Reach out if you have questions!.

Hiring a full-time #PhD student with *full fee waiver* for Home/Overseas applicants to work on *Deep Learning for Medical Video Analysis and Understanding*. All info at the link below. Please share with your networks! .

Full PhD studentships available for Oct 2024 intake at @CityUniLondon! If you are interested in doing research in ML/AI applied to medical images and health data, please reach out. Deadline for application is 29th Jan!. Here all the info:.

We are looking for a lecturer to join @Cit_AI1! If you enjoy doing research and teaching in AI, please consider applying to join a rapidly expanding university in the heart of London.

Pre-print: Work led by Sergio Naval-Marimont @snavalm from our @Cit_AI1 research centre @CityUniLondon. Thanks to our co-authors @MertBTwit, @BernhardKainz1, Vasilis Siomos, @ctzelepis.

Very excited to share DISYRE, our latest leap in unsupervised anomaly detection for medical images. Inspired by diffusion models, our technique replaces Gaussian noise with a gradual synthetic anomaly corruption. DISYRE achieves +33% AP in detecting anomalies in T2 brain MRIs!