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Thomas Kipf

@tkipf
Sr. Staff RS at @GoogleDeepMind. Gemini Omni Team. Priors: GNNs, Structured World Models, Neural Assets, Veo Ingredients/References, Veo Robotics
San Francisco, CA
scholar.google.com/citations?user…
Joined June 2009
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    Thomas Kipf
    @tkipf
    May 4, 2020
    My PhD thesis "Deep Learning with Graph-Structured Representations" is now available for download: hdl.handle.net/11245.1/1b63b9… -- It covers a range of emerging topics in Deep Learning: from graph neural nets (and graph convolutions) to structure discovery (objects, relations, events)
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    Thomas Kipf
    @tkipf
    Jul 6
    If you’re at ICML, make sure to check our poster on “Generation is Required for Data-Efficient Perception”! I won’t be there in person this time, but say hi to @jackhb98 :)
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    Jack Brady
    @jackhb98
    Jul 6
    I’m at #ICML2026 presenting our latest work! (Today/Tue 2 pm; Hall A #4016) Encoder-only approaches (e.g. DINO, SigLIP, JEPA) are the dominant paradigm for visual perception. Yet we provide evidence that using a generative decoder may be key for human-like data efficiency! 🧵👇
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