Eric Arazo

[Paul Albert @PaulAlbert31]

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
https://t.co/AKPLgGEKoC

[Paul Albert @PaulAlbert31]

Very glad to announce that our label noise paper was accepted #ECCV2022. We observe a linear separation between OOD and ID samples in web crawled datasets using unsupervised contrastive learning https://t.co/SMJhXQqi7w. Team: @ArazoEric @kevinmcguinness @oconnorn @insight_centre

[Paul Albert @PaulAlbert31]

I presented my work on using drones to predict herbage quality at the #AgricultureVision workshop @CVPR. A research collab in the @VistaMilk SFI centre between @teagasc and @insight_centre funded by @scienceirel. Great to attend in person again ! Paper: https://t.co/6JQRhX9cVZ

[Eric Arazo @ArazoEric]

@artboxhill @insight_centre Thank you so much for all your help, Hilary! 🙏

[Eric Arazo @ArazoEric]

Excited to present Thursday our #BMVC21 paper on training CNNs under budget constraints. Check it out in the oral session 8 or poster session 4!
Great teamwork @Diego_OrtegoH @oconnorn @kevinmcguinness @insight_centre
BMVC:https://t.co/XThSKrNBxw
arXiV:https://t.co/AHWSv9I5RF

[Insight Research Ireland Centre @insight_centre]

@Diego_OrtegoH "Objective Interpolation Training for Robustness to Label Noise" accepted #CVPR2021 Synthetic & real-world noise in image classification @ArazoEric Paul Albert @oconnorn @kevinmcguinness @DCU: https://t.co/8StitPsp8G Code: https://t.co/Rqy0aUPBIE
#DeepLearning

[Insight Research Ireland Centre @insight_centre]

Insight researcher @Diego_OrtegoH will be presenting "Towards Robust Learning with Different Label Noise Distributions" Jan. 12th, T1.2 at @icpr2020milan
@ArazoEric @oconnorn @kevinmcguinness @insight_centre #ICPR2020 #AI
Paper: https://t.co/NxotFOI4jL
https://t.co/FmkqK55sVp

[Diego Ortego @Diego_OrtegoH]

Happy to announce that our paper "Towards Robust Learning with Different Label Noise Distributions" has been accepted as an oral presentation at @icpr2020milan.
@ArazoEric @oconnorn @kevinmcguinness @insight_centre

Paper: https://t.co/s2avyP2oR7
Code: https://t.co/yj850Lez44

[Diego Ortego @Diego_OrtegoH]

Interested in training DNNs with noisy labels? Check out our new work on Multi-Objective Interpolation Training to deal with synthetic and web noise.
@ArazoEric Paul Albert @oconnorn @kevinmcguinness @insight_centre
Paper: https://t.co/aqhUGmgq7D
Code: https://t.co/Pw8czpvY4d

[Eduardo Fonseca @edfonseca_]

🔊New paper out! "Unsupervised Contrastive Learning of Sound Event Representations". Work done with @Diego_OrtegoH
We learn audio representations by contrasting differently augmented views of sound events.
paper: https://t.co/FEMDmrC5Mb
code (soon): https://t.co/lvH80oALkD
(1/5)

[Eric Arazo @ArazoEric]

We are happy to present our paper "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning" at #IJCNN202 at #WCCI2020 WCCI20. Come along (or e-mail us) if you want to know about some of the challenges of SSL (this evening from 8pm). Code: https://t.co/cZhIqh5rmk

[Eric Arazo @ArazoEric]

"Training Neural Networks for and by Interpolation"
Very clear explanation in the presentation: they propose a way of adapting the learning rate through training. I am looking forward to reading the paper more deeply.

[Eric Arazo @ArazoEric]

That's a good way of sharing papers @alexhdezgcia!
I am glad of participating as a volunteer in #ICML2020 , I had the chance to help together with hundreds of volunteers in a great online event.

I will leave here some of the papers I have been looking at.

[Alex Hernandez-Garcia @alexhdezgcia]

At #ICML2020 I have decided to focus on a small number of papers and really try to understand them and engage with the authors and other participants in the presentations. As opposed to trying to see a lot of posters.

I will be posting here the most interesting papers I find.

[Eric Arazo @ArazoEric]

"Data-Efficient Image Recognition with Contrastive Predictive Coding"
Nice insights on CPC and interesting experiments (especially with all the self-supervised approaches that are coming out these days).

[Kevin McGuinness @kevinmcguinness]

If you are attending #ICML2019 and are interested in learning in the presence of label noise, come see our poster on "Unsupervised Label Noise Modeling and Loss Correction" https://t.co/yLh90GNbuR this evening from 6:30pm. @oconnorn @ArazoEric @insight_centre

[Eric Arazo @ArazoEric]

Our upcoming #ICML2019 paper "Unsupervised Label Noise Modeling and Loss Correction" is now on arXiv https://t.co/dnQtI1OU8a. New SoTA in CIFAR10/100 under high-levels of noise using Beta mixtures to model & correct losses. Code: https://t.co/UBoucR0ImS @oconnorn @kevinmcguinness

[Xavi Giró @DocXavi]

It is official now: @BCN_ai is born. Long life to #BCNai !