Research Scientist at @Meta | AI and neural interfaces | Interested in data augmentation, generative models, geometric DL, brain decoding, human pose, …
Paris, France
Joined October 2015
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Inferring 3D human poses from video is highly ill-posed because of depth ambiguity.
Our work accepted to #NeurIPS2024, ManiPose, gets one step closer to solving this, by leveraging prior knowledge about poses topology and cool multiple-choice learning techniques.
Think your decoding model can read hand-poses from an EMG wristband? Come show us your 💪 and break our baselines on a real-world industry problem!
No cameras. No gloves. Reconstructing hand pose from surface EMG at the wrist with a @Meta Neural Band.
It's track 4 in our NeurIPS 2026 Neural Interfaces competition. Real wearable data and real $$$ for the winners!
👉 neural-interfaces26.github.i…
As my team says 👋🤙✌️🤌🖐️!
Cédric Rommel 🦋 retweeted
We’re sharing the next major milestone in our non-invasive brain-to-text decoder research: Brain2Qwerty v2.
Building on v1, which was published today in @Nature, Brain2Qwerty v2 is the highest-performing end-to-end pipeline capable of real-time sentence decoding from raw brain signals. It advances beyond character-level performance to decoding words and semantics, enabling accuracy for overall communication.
We believe this research has the potential to make a real difference for the millions of people who suffer from brain lesions or disorders that prevent them from communicating.
🧵👇
Decoding typing from brain activity — no surgery needed. Brain2QwertyV2, led by @JarodLevy and @LucyZ47712090, narrows the gap with invasive BCIs using LLMs on MEG and paves the way toward real-time language decoding! Proud to have collaborated with this talented team!
Cédric Rommel 🦋 retweeted
Human-Computer Input via a Wrist-Based sEMG Wearable
meta.com/blog/quest/surface-…
Yet another great work on multi-hypothesis learning by @VLetzelter accepted to #NeurIPS2024 ! In this paper they show that simulated annealing can help to make the winner-takes-all loss more stable and robust, demonstrating its useful in many ill-posed real-world applications!
Working on ill-posed machine learning tasks, interested in multi-heads neural networks and data #uncertainty quantification ?
Sharing here our latest research, which will be presented at @NeurIPSConf in December.
Our team at @RealityLabs is also open-sourcing two EMG datasets at #NeurIPS2024 :
emg2pose and emg2qwerty
Check it out if you want to try predicting hand poses and typed text from a new challenging data modality!
emg2pose: Hand pose estimation anywhere with neuromotor interfaces
A Dataset and Benchmark @ Neurips 2024 arxiv.org/abs/2412.02725v1
See blog: ai.meta.com/blog/open-sourci…
If you’re at #Neurips2024 next week, come meet us in poster session 3 on Thu 12 Dec 11 a.m.!
Or at our oral presentation during the @neur_reps workshop on Saturday 14th!
Paper: arxiv.org/abs/2312.06386
Github: github.com/cedricrommel/mani…
✨Joint work with the amazing @VLetzelter , @nemka_ , @RenaudMarlet, @quobbe , @ptrkprz and Eduardo Valle✨
If you are at #ICML2024 , come chat with @VLetzelter , David and I about conditional density estimation and ill-posed ML tasks this afternoon !
Poster session 4 - 1:30pm - poster # 1506
Interested in ill-posed learning tasks, uncertainty prediction, conditional density estimation or multi-head deep neural networks ?
In our new paper, accepted at #ICML24, we tackle these challenges by exploring the Winner-Takes-All (WTA) training scheme.
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I’ll be attending #ICML2024 next week to present this excellent work led by @VLetzelter ! Looking forward to chat about ill-posed machine learning tasks, data augmentation, pose estimation, eeg decoding or anything else ML at the poster session or around some coffee !
Interested in ill-posed learning tasks, uncertainty prediction, conditional density estimation or multi-head deep neural networks ?
In our new paper, accepted at #ICML24, we tackle these challenges by exploring the Winner-Takes-All (WTA) training scheme.
[1/n]