Our paper: "Is your noise correction noisy? PLS: Robustness to label noise with two stage detection" was accepted at #WACV2023 ! We detect incorrect true label guesses using our pseudo-loss to combat label noise in image classification datasets arxiv.org/abs/2210.04578

I just presented my latest work on computer vision in the presence of label noise to the Insight Smart Surrounding showcase #InsightSSS22 Dublin City University. A research collaboration between by VistaMilk Research Ireland Centre and Insight Research Ireland Centre @scienceirel. Great to see everyone in person !

Just out of an intense poster session #ECCV2022 on Tel Aviv. We detect two forms of label noise using unsupervised contrastive leaning. Paper: arxiv.org/abs/2207.01573. A fruitful collaboration between Insight Research Ireland Centre and VistaMilk Research Ireland Centre funded by @scienceirel

The code for our latest label noise paper PLS arxiv.org/abs/2210.04578 was just released on github github.com/PaulAlbert31/P…. Feel free to reproduce our results and test on your own noisy dataset ! Team: Eric Arazo tarunkrishna Prof. Noel O'Connor (he/him) Kevin McGuinness

Congratulations to our researchers Paul Albert and Hannah Masterson on winning awards for best oral presentation at the VistaMilk industry day 👏 @scienceirel Dept of Agriculture, Food and the Marine

Congrats to Paul Albert who successfully defended his PhD thesis "Deep Learning for Computer Vision constrained by Limited Supervision". Jointly-supervised with Kevin McGuinness. Thanks to examiners @fosterjendublin & Prof Yannis Patras of QMUL Electronic Engineering and Computer Science VistaMilk Research Ireland Centre Insight Research Ireland Centre

Excited to announce that the codebase for our #neurips2024 paper Knowledge Composition using Task Vectors with Learned Anisotropic Scaling (arxiv.org/abs/2407.02880) is now available. In this paper, we showed how to combine or transfer the knowledge across different models. [1/6]

Check out our new work freshly accepted at #neurips2024 where we improve knowledge composition and few-shot generalization in large transformer models using learnt anisotropic scaling of task vectors. Paper: arxiv.org/abs/2407.02880 Code: github.com/fredzzhang/atl…