Julien Gustin (@gustin_julien) 's Twitter Profile
Julien Gustin

@gustin_julien

Msc. Data science - ULiege

ID: 1172884408807907329

linkhttps://github.com/Julien-Gustin calendar_today14-09-2019 14:47:08

109 Tweet

40 Followers

104 Following

Scott Condron (@_scottcondron) 's Twitter Profile Photo

Here's an animation of a PyTorch DataLoader. It turns your dataset into a shuffled, batched tensors iterator. (This is my first animation using Manim Community, the community fork of Grant Sanderson's manim) Here's a little summary of the different parts for those curious: 1/5

Aurimas Griciลซnas (@aurimas_gr) 's Twitter Profile Photo

How do you build a ๐—Ÿ๐—Ÿ๐—  ๐—ฏ๐—ฎ๐˜€๐—ฒ๐—ฑ ๐—–๐—ต๐—ฎ๐˜๐—ฏ๐—ผ๐˜ ๐˜๐—ผ ๐—พ๐˜‚๐—ฒ๐—ฟ๐˜† ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ฃ๐—ฟ๐—ถ๐˜ƒ๐—ฎ๐˜๐—ฒ ๐—ž๐—ป๐—ผ๐˜„๐—น๐—ฒ๐—ฑ๐—ด๐—ฒ ๐—•๐—ฎ๐˜€๐—ฒ? Letโ€™s find out. First step is to store the knowledge of your internal documents in a format that is suitable for querying. We do so by embedding it using an

How do you build a ๐—Ÿ๐—Ÿ๐—  ๐—ฏ๐—ฎ๐˜€๐—ฒ๐—ฑ ๐—–๐—ต๐—ฎ๐˜๐—ฏ๐—ผ๐˜ ๐˜๐—ผ ๐—พ๐˜‚๐—ฒ๐—ฟ๐˜† ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ฃ๐—ฟ๐—ถ๐˜ƒ๐—ฎ๐˜๐—ฒ ๐—ž๐—ป๐—ผ๐˜„๐—น๐—ฒ๐—ฑ๐—ด๐—ฒ ๐—•๐—ฎ๐˜€๐—ฒ?

Letโ€™s find out.

First step is to store the knowledge of your internal documents in a format that is suitable for querying. We do so by embedding it using an
Rรฉmi Flamary ๐Ÿฆ‹ (@rflamary) 's Twitter Profile Photo

We are looking for a research engineer to work on domain adaptation and transfer learning ร‰cole polytechnique near Paris. Come with us to do research, open source Python software and benchmarks. Contact me by email if interested. Please RT (free users need to help each other).

PA ๐Ÿ•บ๐Ÿป (@domingo) 's Twitter Profile Photo

Allez hop pti giveaway sur mon compte รงa faisait longtemps, on vous fait gagner un vรฉlo รฉlectrique dโ€™une valeur de 2500โ‚ฌ avec EDF ! Pour participer, RT/like le tweet et follow PA ๐Ÿ•บ๐Ÿป & @energiedusport, tirage au sort le 04/10 โšก #CollaborationCommerciale

Allez hop pti giveaway sur mon compte รงa faisait longtemps, on vous fait gagner un vรฉlo รฉlectrique dโ€™une valeur de 2500โ‚ฌ avec EDF ! Pour participer, RT/like le tweet et follow <a href="/Domingo/">PA ๐Ÿ•บ๐Ÿป</a> &amp; @energiedusport, tirage au sort le 04/10 โšก #CollaborationCommerciale
Aerospacelab (@aerospacelab_) 's Twitter Profile Photo

Meet #PVCC's first image ๐Ÿ˜ Ten years after its siblings, #PVCC's instrument took its first in-orbit multispectral image ๐ŸŒ Those first space steps, taken only 3๏ธโƒฃ days after launch, allow to stretch the impressive swath of 350km and survey Switzerland's vegetation in one sweep!

Meet #PVCC's first image ๐Ÿ˜

Ten years after its siblings, #PVCC's instrument took its first in-orbit multispectral image ๐ŸŒ

Those first space steps, taken only 3๏ธโƒฃ days after launch, allow to stretch the impressive swath of 350km and survey Switzerland's vegetation in one sweep!
Google DeepMind (@googledeepmind) 's Twitter Profile Photo

Presenting GraphCast: our state-of-the-art AI model delivering 10-day weather forecasts with unprecedented accuracy in under one minute. ๐ŸŒฆ๏ธ It can even help predict the potential paths of cyclones further into the future. Here's how it works. ๐Ÿงต dpmd.ai/presenting-graโ€ฆ

Walid BOUSSELHAM (@bousselhamwalid) 's Twitter Profile Photo

Happy to announce our latest paper: ย Grounding Everything: Emerging Localization Properties in Vision-Language Transformers ๐ŸŽ‰๐ŸŽ‰๐ŸŽ‰ GEM allows a training-free adaptation of Vision-Language models (e.g., CLIP ...) to perform zero-shot open-vocabulary segmentation.

Franรงois Rozet (@francoisrozet) 's Twitter Profile Photo

I'll be presenting Score-based Data Assimilation at NeurIPS Conference on December 12th ๐Ÿฅณ Come talk about generative models, score priors, Markov blankets, dynamical systems and much more! ๐Ÿ“œ arxiv.org/abs/2306.10574 ๐Ÿ‘จโ€๐Ÿ’ป github.com/francois-rozetโ€ฆ ๐Ÿ’ฌ neurips.cc/virtual/2023/pโ€ฆ

Naina Chaturvedi (@nainachaturved8) 's Twitter Profile Photo

โœ…Most important Training and Optimization Techniques for Transformers in ML - Explained in Simple terms. A quick thread ๐Ÿ‘‡๐Ÿป๐Ÿงต #MachineLearning #Coding #100DaysofCode #deeplearning #DataScience PC : Research Gate

โœ…Most important Training and Optimization Techniques for Transformers in ML - Explained in Simple terms.         
A quick thread ๐Ÿ‘‡๐Ÿป๐Ÿงต
#MachineLearning #Coding #100DaysofCode #deeplearning #DataScience
PC : Research Gate
Nicolas Gonthier (@nicaogr) 's Twitter Profile Photo

The FLAIR dataset ๐Ÿ›ฉ๏ธ๐Ÿ›ฐ๏ธ is also available on Hugging Face : - over 20 billion annotated pixels of very high resolution aerial imagery at 0.2 m spatial resolution - along with Sentinel-2 satellite 1-year time series with 10 spectral band at 10m huggingface.co/datasets/IGNF/โ€ฆ

The FLAIR dataset ๐Ÿ›ฉ๏ธ๐Ÿ›ฐ๏ธ is also available on Hugging Face :
- over 20 billion annotated pixels of very high resolution aerial imagery at 0.2 m spatial resolution 
- along with Sentinel-2 satellite 1-year time series with 10 spectral band at 10m

huggingface.co/datasets/IGNF/โ€ฆ
Giorgia Ramponi (@gio_ramponi) 's Twitter Profile Photo

Exciting opportunity! Join my new research group at the University of Zurich as a PhD candidate in Reinforcement Learning. Contribute to cutting-edge AI research and shape the future of the field ๐Ÿ”ฅ To apply follow the instructions on my website: gioramponi.github.io #UZH #RL

antoine (@antoinelouis_) 's Twitter Profile Photo

Need a dense multi-vector retrieval model in your language? We've got you covered with ColBERT-XM, a new modular retriever that supports 81+ languages and can easily be extended to many more. [1/4] ๐Ÿ“‘ Paper: arxiv.org/abs/2402.15059 ๐Ÿค— Model: huggingface.co/antoinelouis/cโ€ฆ

Aerospacelab (@aerospacelab_) 's Twitter Profile Photo

๐Ÿš€ Yesterday, March 4th, marked a momentous occasion as our team gathered to witness the successful deployment of four of our satellites into orbit. After months of hard work and meticulous planning, we watched with anticipation as our birds were released from Falcon 9 for

๐Ÿš€ Yesterday, March 4th, marked a momentous occasion as our team gathered to witness the successful deployment of four of our satellites into orbit.

After months of hard work and meticulous planning, we watched with anticipation as our birds were released from Falcon 9 for
clem ๐Ÿค— (@clementdelangue) 's Twitter Profile Photo

We collaborated with the European Space Agency to open-source the largest ever earth observation dataset: Major TOM Core! About half of the entire planet is covered. That's 2,245,886 patches of 1068 x 1068 pixels. At 10m resolution, we've got 256 million square km with over 2.5

We collaborated with the European Space Agency to open-source the largest ever earth observation dataset: Major TOM Core!

About half of the entire planet is covered. That's 2,245,886 patches of 1068 x 1068 pixels. At 10m resolution, we've got 256 million square km with over 2.5
Julien Gustin (@gustin_julien) 's Twitter Profile Photo

I strongly believe AI papers should standardize including model size and benchmarking model speed against others. In my opinion, this is more crucial than gaining a few percentage points on a dataset, especially from a production point of view.