Multimodal Representation Learning @ ICLR23 @mrlworkshop
First workshop on multimodal representation learning, to be held in May as part of ICLR 2023 in Kigali, Rwanda (virtual). mrl-workshop.github.io/iclr-2023/ Kigali, Rwanda Joined December 2022-
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⏰Our virtual workshop will be happening tomorrow ! Come join our discussions and hear from our amazing line up of speakers including Kristen Grauman, Zeynep Akata (@zeynepakata), Arsha Nagrani (@NagraniArsha), N. Siddharth & Paul Liang! Schedule: iclr.cc/virtual/2023/w…
Only a few weeks away from #iclr2023! We can't wait to see everyone at our virtual workshop :) we have an amazing line up of speakers which we will announce in the upcoming weeks -- stay tuned!
Decisions are out *now*! Whether your paper is accepted or not, we would love to see you sharing your work here ☺️ Massive congratulations to authors of all accepted papers and hope everyone found the reviews helpful!
Submission deadline is *today* 🗓️! Are you all done and dusted, or secretly hoping the Earth is bigger so AOE deadline hits later in the day? 🌍☀️
And, of course, 3rd Jan means 3rd Feb. Looking forward to your submissions!
And, of course, 3rd Jan means 3rd Feb. Looking forward to your submissions!
We have extended our deadline for 3 days to 3rd Jan AOE! Keep those submissions coming 👀
It is time to submit your work, pre-prints or preliminaries ideas on multi-modal representation learning!
It is time to submit your work, pre-prints or preliminaries ideas on multi-modal representation learning!
We are in the process of confirming our final speaker for our multimodal representation learning workshop @iclr_conf, and we are curious to hear your opinion: who do you think we should invite? Self-recommendations are more than welcomed 🤗
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Probably the best non-fake video call background I'll ever have 😌 Come join us in gathertown for our poster session @mrlworkshop! Gather Town Link: tinyurl.com/mrl2023 Password: mrl_workshop_2023!
@egrefen @mattshumer_ @cohereai I thought language models no longer repeat the language models no longer repeat the language models no longer repeat the language models no longer repeat the language models no longer repeat the language models no longer repeat the language models no longer repeat the same thing.
@mrlworkshop I assume mean 3 Feb? Could you please update the website and/or OpenReview?
I expect about 30% of NeurIPS papers this year to be something like “towards solving finger-collapse in diffusion-based generative models using doubly conditioned augmented hypernetworks”
@mrlworkshop @javaloyML @iclr_conf Suggestion: x.com/pranavrajpurka…
Delighted to share our @NatureMedicine review on multimodal biomedical AI! We cover personalized medicine, digital clinical trials, remote monitoring, pandemic surveillance, digital twin technology & health assistants. With @EricTopol @jn_acosta nature.com/articles/s4159…
It is time to submit your work, pre-prints or preliminaries ideas on multi-modal representation learning!
Is having multiple modalities a blessing or a curse? What is a good representation? Let's find out together! We are proud to announce the 1st hybrid workshop on Multimodal Representation Learning at #ICLR2023 (@iclr_conf) 🚀 More info: mrl-workshop.github.io/iclr-2023/
@mrlworkshop unfortunately not in person, but will attend virtually!
This is going to be the principal forum for #research in #multimodal and #multitask #generative modeling. Do not miss it! #ICLR2023 #Rwanda #ML #AI
So thrilled to see so many interesting work accepted to #ICLR2023, can't wait to see you all in Kigali! That said -- if you work did not get a chance to shine at the main conference, consider submitting to our multimodal learning workshop! Submission open till 30 Jan ⌛️
[1/6] What is an NMT model "thinking" when it hallucinates? Are there any internal symptoms that may flag a hallucination? Our new paper "Understanding and Detecting Hallucinations in Neural Machine Translation via Model Introspection" is out! arxiv.org/abs/2301.07779
📢 Call for Blog Post at ICLR 2023 📢 Submissions are OPEN, deadline on Feb 2nd. Detailed instructions can be found on the main website of the track: iclr-blogposts.github.io/2023/call PCs are @gauthier_gidel, @velythyl, @busycalibrating, @joanbruna and @vernadec
Diffusion models + causality? Our new paper ACCEPTED to ICLR 2023 explores how to do causal discovery using diffusion models for topological ordering! Go check it out! arxiv.org/abs/2210.06201 Code is available: github.com/vios-s/DiffAN (main code is under 200 python lines)
Who knew people were so interested in generative models @jmtomczak 😉
Just your friendly neighbourhood workshop looking for solid submissions 👀 spread the words!
So thrilled to see so many interesting work accepted to #ICLR2023, can't wait to see you all in Kigali! That said -- if you work did not get a chance to shine at the main conference, consider submitting to our multimodal learning workshop! Submission open till 30 Jan ⌛️
In a master's seminar @AIatLMU we (@assenmacher_mat @BBischl @Hvingelby @daniel_schalk) wrote an overview book on multimodal deep learning with some motivated students that hopefully provides a solid warm intro: Online: slds-lmu.github.io/seminar_multim… Arxive: arxiv.org/abs/2301.04856
Multimodal Deep Learning Of all the areas in AI, multimodal deep learning is the one I am most excited about. If you are building in this space, I recommend you check out this new book on multimodal deep learning that just landed on arXiv. arxiv.org/abs/2301.04856
When you wake up to read this email from ICLR 😍 Congrats and thanks for the collaboration @davidwromero @davidmknigge @_albertgu @egavves @erikjbekkers M. Hoogendorn & JJ Sonke! 🙏 Paper: openreview.net/forum?id=ZW5aK…
Our work on robust and automatic GNN layer selection has been accepted at #ICLR2023 🥳🥳 Excited to see you all in Kigali!
📰Excited to introduce our latest paper “Learnable Graph Convolutional Attention Networks”! arxiv.org/abs/2211.11853 Joint work by the awesome team @javaloyML, @amitzeani, and @IValeraM. 🔎 Sidenote: Let's meet at #NeurIPS2022! 🧵 (1/n)
Multimodal Deep Learning Of all the areas in AI, multimodal deep learning is the one I am most excited about. If you are building in this space, I recommend you check out this new book on multimodal deep learning that just landed on arXiv. arxiv.org/abs/2301.04856
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