Cédric Rommel 🦋

313 posts

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Cédric Rommel 🦋

Cédric Rommel 🦋

@ccrommel

Research Scientist at @Meta | AI and neural interfaces | Interested in data augmentation, generative models, geometric DL, brain decoding, human pose, …

Paris, France Katılım Ekim 2015
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Cédric Rommel 🦋
Cédric Rommel 🦋@ccrommel·
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.
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Cédric Rommel 🦋
Cédric Rommel 🦋@ccrommel·
@andrewgwils @micahgoldblum In the same vein, I also feel that great ideas are often simple in some sense, and can easily be misjudged as being simplistic. Also scientists (and reviewers) are skeptical “by design” :)
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Andrew Gordon Wilson
Andrew Gordon Wilson@andrewgwils·
@micahgoldblum That's certainly part of it. I suspect it's also partly a combination of: (1) creative or conceptually oriented works being harder to evaluate; (2) competitiveness. Great works are often bold in some way, which can trigger envy, insecurity, or defensiveness, even subconsciously.
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Andrew Gordon Wilson
Andrew Gordon Wilson@andrewgwils·
Many of the greatest papers, now canonical works, have a story of resistance, tension, and, finally, a crucial advocate. It's shockingly common. Why is there a bias against excellence? And what happens to those papers, those people, when no one had the courage to advocate?
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Cédric Rommel 🦋
Cédric Rommel 🦋@ccrommel·
@PessoaBrain Not so much out of context honestly, and probably annoyed most of the neuro part of the public 😅 I think this slide came up when justifying the “scale is all you need” hypothesis. But he did insist on the assumption of the first line
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Luiz Pessoa
Luiz Pessoa@PessoaBrain·
This would be funny if it weren't sad... Coming from the "giants" of AI. Or maybe this was posted out of context? Please clarify. I can't process this...
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Cédric Rommel 🦋
Cédric Rommel 🦋@ccrommel·
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!
Victor Letzelter@VLetzelter

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.

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Cédric Rommel 🦋
Cédric Rommel 🦋@ccrommel·
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.
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Cédric Rommel 🦋
Cédric Rommel 🦋@ccrommel·
Oh boy, something definitely happened in 2022 ! 😅
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Cédric Rommel 🦋
Cédric Rommel 🦋@ccrommel·
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
Victor Letzelter@VLetzelter

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]

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Cédric Rommel 🦋
Cédric Rommel 🦋@ccrommel·
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 !
Victor Letzelter@VLetzelter

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]

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