Top Tweets for #ICLR2016
🤓 How do LVLM/LMMMs reason about space and time?
This was the central question of our #ICLR2016 paper, “Linear Mechanisms For Spatiotemporal Reasoning In Vision Language Models”. I’m very excited to finally share it:D 🥳🥳
A thread: [1/7]
![RaphiKang's tweet photo. 🤓 How do LVLM/LMMMs reason about space and time?
This was the central question of our #ICLR2016 paper, “Linear Mechanisms For Spatiotemporal Reasoning In Vision Language Models”. I’m very excited to finally share it:D 🥳🥳
A thread: [1/7] https://t.co/ZT0TBXnshW](https://pbs.twimg.com/media/G_oqwCNbAAAVlFi.jpg)
The GRaM workshop is coming back at #ICLR2016!
Very much looking forward to exciting discussions on geometry, representation learning and generative modeling!
📢 GRaM workshop is back!! This time at #ICLR2026
🌟Excited to be in Brazil 🇧🇷!
More information coming soon!
@iclr_conf @GRaM_org_
Similar study was published at #ICLR2016 workshop:
Neural Network Training Variations in Speech and Subsequent Performance Evaluation
https://t.co/CQolA1Vr6i
Our #iclr2016 #RNN paper quoted as seminal one for session based learning for #recsys at #dlrs2017 by @ruoccoma #recsys2017 @Gravityrd
#DeepLearning Trends at #ICLR2016: https://t.co/M8R8R1XBlC #BigData #DataScience #MachineLearning #ComputerVision
Base code 4 session b #recommendation with #RNN #deeplearning from #iclr2016 @balazshidasi @alex_k #recsys2016 https://t.co/9jrS0Ob8EU
RNN based session recommendations building on our #iclr2016 paper @balazshidasi @Gravityrd #recsys2016 #dlrs2016
#iclr2016 Judge Thomson - key to foreign lawyer admission is getting information on character and fitness. Regulator cooperation essential.
very cool talk: "Do different neural networks learn the same representations?" https://t.co/Jy0V5DEQFI #iclr2016
.@Luke_Metz highlights some of his #ICLR2016 takeaways, with a focus on adversarial models and optimization: https://t.co/zVBnkhScqV
Also, all 20 #DeepLearning lectures from #iclr2016 were recorded, and you can watch them here: https://t.co/WlmiCvBHrZ. For Free.
There's no better time to learn about #DeepLearning. Every #ICLR2016 paper is on Arxiv & linked from their schedule: https://t.co/MWNAwt1kgU
.@DeepMindAI's Neural Programmer Interpreters can write algorithms! A #ICLR2016 best paper:
https://t.co/JB0htsD364
.@quantombone is the Lead Software Engineer in #DeepLearning at @MagicLeap. It's awesome to hear #ICLR2016 had much open academic innovation
Following @dirk_hovy's awesome tradition, my #ICLR2016 fabric poster was turned into a hipster bag :D
Tombone's Computer Vision Blog: Deep Learning Trends at #ICLR2016 https://t.co/rbDyYmXk2j #computervision #deeplearning @quantombone
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