Excited to share that our paper 'Weisfeiler and Leman go Hyperbolic: Learning Distance Preserving Node Representations' with @giannis_nikole and @mvazirg has been accepted at #AISTATS2023@aistats_conf !
Next Tuesday at noon, I will be presenting some of our work in the area of Graph Representation Learning. Please come join us if you are in the Saclay region.
Thank you very much @tomamoral and Victor-Emmanuel Brunel for the invitation and organisation!
#EMNLP2022
Excited to present my paper “Questioning the Validity of Summarization Datasets and Improving Their Factuality” in poster session 8 tomorrow 9:00-10:30 am. #NLProc
Many thanks to my advisors @mvazirg and @ChloeDClavel!
Thrilled to announce that our paper "Graph Ordering Attention Networks" has been accepted at @RealAAAI#AAAI2023. Many thanks to my amazing co-authors @JLutzeyer , @GDasoulas and my advisor @mvazirg . (1/n)
🆙We are super excited to have @JLutzeyer continue in our team as Assistant Professor, after two years of brilliant postdoctoral research!!!
🎉A great evolution for DaSciM!!!
Starting September, I will be working as an Assistant Professor in @dascim_polytech@LIX_lab@Polytechnique@IP_Paris_!
I am excited by the prospect of working with graphs & GNNs for many years to come and to keep interacting with the brilliant @IP_Paris_ students & colleagues.
- "Mass Enhanced Node Embeddings for Drug Repurposing" by @giannis_nikole , @MichailChatzia1 accepted in the ICML - Workshop on Computational Biology
Congratulations to all!
Congratulations to @giannis_nikole and @GDasoulas for their paper: “Permute Me Softly: Learning Soft Permutations for Graph Representations” accepted for publication to the prestigious TPAMI journal!!! Bravo!
Also congrats to the authors of previous papers accepted this month:
- "Modularity-Aware Graph Autoencoders for Joint Community Detection and Link Prediction" by @gsalhagalvan@JLutzeyer@GDasoulas accepted for publication in Elsevier's Neural Networks journal
Tomorrow 12:30-14:00 CET, @cmwu8, @melaseddik, @mvazirg and I will present our joint work at #AISTATS2022. Please join us there; we are excited to meet you!
https://t.co/f9AQpgSggu
1/2
Yesterday I had the pleasure of speaking at the workshop on "Recent Advances in Graph Machine Learning" (https://t.co/PIHG0OcBsB). I would like to thank @n_keriven & E. Oyallon for the smooth organisation.
In case you are curious, here are my slides: https://t.co/kW8Ri00gPS
[#Research] We are glad to co-organise the seminar series "Law, Society & AI", result of joint effort between @IP_Paris_ and @HECParis.
Talks take place online as well as on the @ParisSaclay campus. #AI#LegalTech
Check out the link here👉https://t.co/RlbQL1HHzE
Great paper and thread!
- 😮that super simple MSE loss works vs. BEiT-style dVAE (multi-modal) cross-entropy
- <3 efficiency of asymmetric encoder/decoder
- 👏detailed training recipes
- +1 v curious about dataset size scaling
- bit of lack of commentary on test-time protocol
[#EVENT] A huge thanks to Prof. #JohnIoannidis for his inspirational talk on "Meta-Research and the Quest for Better Science" @Polytechnique @IP__Paris 👏
A memorable afternoon full of enlightening insights and meaningful exchanges🎊🎆
#BREAKING We are super excited to host Prof. #JohnIoannidis, physician, writer and one of the top cited scientists in the world. He will give a talk entitled “Meta-Research and the Quest for Better Science” on November 10th @Polytechnique. Save the date!
👉https://t.co/GnRH7QUuOe
Significant French language resources learned from large scale web/twitter crawl. Static/contextual word embeddings, N-grams, end2end demos (summarisation, title generation). Thanks to
@AgenceRecherche
chair HELAS funding https://t.co/AWYIu9ATmD…
@IP__Paris @Polytechnique