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Andrei Bursuc
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@abursuc

Andrei Bursuc

@abursuc
Research scientist @valeoai | Teaching @Polytechnique @ENS_ULM | Alumni @upb1818 @Mines_Paris @Inria @ENS_ULM | Feedback: admonymous.co/abursuc
Paris, France
abursuc.github.io
Joined November 2008
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  • Pinned
    @abursuc
    Andrei Bursuc
    @abursuc
    Jan 9
    The unreasonable magic of simplicity! Meet DrivoR (Driving on Registers): our latest end2end autonomous driving model. We teared down complex dependencies & modules from current models to obtain a pure Transformer-based SOTA driving agent (NAVSIM v1 & v2, HUGSIM). Find out more👇
    @EllingtonKirby
    Ellington Kirby
    @EllingtonKirby
    Jan 9
    1/🧵 Q: Can we have both a simple and SOTA architecture in autonomous driving? R: Yes! 😍 Introducing Driving on Registers (DrivoR): a pure Transformer backbone that achieves SOTA results in NAVSIM v1 / v2 and closed-loop HUGSIM evaluation. Here is how 👇
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  • @abursuc
    Andrei Bursuc
    @abursuc
    1h
    Join us for Uncertainty Quantification for Computer Vision Workshop in room Quality View Hotel - Helsingborg. We’re about to start and we have a few seats lets #eccv2026
    @abursuc
    Andrei Bursuc
    @abursuc
    Sep 6
    🛟 Reliable & reliability folks @eccvconf! Join our workshop on Uncertainty Quantification for Computer Vision #eccv2026 We have a super lineup of speakers (from computer vision to MLLMs & LLMs) and cool posters. 🗓️ Date: Tue Sep 8 📌Room: Quality View Hotel - Helsingborg
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  • @abursuc
    Andrei Bursuc
    @abursuc
    2h
    Alright @eccvconf! Let’s go! PS: Don’t get intimidated by the long queue, it advances fast #eccv2026
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  • @abursuc
    Andrei Bursuc
    @abursuc
    Sep 6
    🛟 Reliable & reliability folks @eccvconf! Join our workshop on Uncertainty Quantification for Computer Vision #eccv2026 We have a super lineup of speakers (from computer vision to MLLMs & LLMs) and cool posters. 🗓️ Date: Tue Sep 8 📌Room: Quality View Hotel - Helsingborg
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  • @abursuc
    Andrei Bursuc
    @abursuc
    Sep 5
    Super proud of Pictura: our GPU-accelerated multi-agent driving simulator that renders super-fastly the ego-centric view of every agent at every time step. This enables us now to train driving policies with self-play at scale without privileged information. Find out more below 👇
    @yuanyinnn
    Yuan Yin
    @yuanyinnn
    Sep 5
    Can a car learn to drive by playing against itself, using only its cameras? Self-play driving agents have relied on a shortcut: perfect knowledge of every vehicle's position and speed, even the ones they can't see. A real car never gets that. We take the shortcut away. 🧵
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