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Dino Sejdinovic @sejDino

Professor of Statistical Machine Learning at @UniofAdelaide, @TheAIML. Previously at @OxCSML, @GatsbyUCL, @BristolUni. sejdino.github.io Adelaide, Australia Joined December 2011
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Dino Sejdinovic retweeted
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Natalia Ares group @NAresgroup

4 months ago

🤩Great article about our recent paper in the University news! 🥳 @oxengsci @mplsoxford @NewCollegeOx @UniofOxford ox.ac.uk/news/2024-01-1…

Dino Sejdinovic retweeted
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Veit D. Wild @vdwild

5 months ago

Come to my Neurips talk today! I'll talk about generalised variational inference and the Wasserstein gradient flow. @sejDino @SGhalebikesabi @LauchLab I'll also bei at the poster session today at 10.45 at stand 1301.

Dino Sejdinovic retweeted
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Lewis Mitchell @lewis_math

5 months ago

A coup and a real treat to see Xiao-Li Meng present his first talk on wine, and at a National Wine Centre to kick off day 2 of #ADSN2023! ⁦@AustralianData⁩ ⁦@UniofAdelaide⁩ ⁦@UofA_SET⁩

Dino Sejdinovic retweeted
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AUS Data Science Network @AustralianData

5 months ago

What a turnout! It’s so great to see so many amazing people at our annual ⁦@AustralianData⁩ Science Network Conference - this year being hosted by the ⁦@UniofAdelaide⁩ Data Science Centre at ⁦@NatWineCentre⁩ in Adelaide.#ADSN2023

Dino Sejdinovic retweeted
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Australian Institute for Machine Learning @TheAIML

5 months ago

Published today — Responsible AI: Your questions answered Developed in partnership with @ATSE_au, this special report offers an insight into the world of responsible AI and the opportunities it presents to Australia. #AustraliasAIMonth bit.ly/47LnFdW

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Dino Sejdinovic @sejDino

5 months ago

Can't say I entirely agree, but this definitely puts things into perspective.

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Dan Roy @roydanroy

5 months ago

Can't say I entirely agree, but this definitely puts things into perspective.

Dino Sejdinovic retweeted
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Jeremias Knoblauch @LauchLab

6 months ago

@vdwild @SGhalebikesabi @sejDino and I rigorously connected Bayesian methods to deep ensembles using Wasserstein gradient flows! Our results are summarised in a recent NeurIPS oral paper (arxiv.org/abs/2305.15027), a 30-minute talk (tinyurl.com/2tt5xdmz), and below:

Dino Sejdinovic retweeted
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Peyman Milanfar @docmilanfar

8 months ago

hyper-parameter tuning

Dino Sejdinovic retweeted
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Shahine Bouabid @shbouabid

9 months ago

📢Happy to share our latest work with @sejDino @DWatsonParris : FaIRGP, an emulator that combines the robustness of simple climate models and the flexibility and uncertainty quantification of GPs. 📰Preprint: arxiv.org/abs/2307.10052 💻Code: github.com/shahineb/FaIRGP ⏬More below

Dino Sejdinovic retweeted
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Lewis Mitchell @lewis_math

10 months ago

Kicking off the Adelaide Data Science Centre’s workshop on sampling and response bias correction at @UniofAdelaide — great to see people from inside the Uni and out here in the room (with more online!). Thanks to @jazzystats and @sejDino for organising!

Dino Sejdinovic retweeted
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Michael A Osborne @maosbot

10 months ago

For me "back to normal" does NOT mean "no more masks", it means "not being repeatedly infected by a virus that causes brain damage"

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Dino Sejdinovic @sejDino

11 months ago

Save the dates for the Australian Data Science Network Conference, to he held in Adelaide, 7-8 December 2023: australiandatascience.net/event/2023-ads…

Dino Sejdinovic retweeted
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Shahine Bouabid @shbouabid

11 months ago

I've had a lot of discussions about the reasons why I don't want to fly to Honolulu for #ICML23, so I thought it'd be interesting to compile recurring themes from these conversations in a thread. 1/n

Dino Sejdinovic retweeted
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Siu Lun Chau @Chau9991

11 months ago

1/3 🚨 Excited to share our latest work on GP x Explainability with @krikamol and @sejDino ! (1) We developed GP-SHAP to explain GPs as stochastic Shapley values, and (2) formulate explanation functions as GPs with our Shapley prior. Check it out! arxiv.org/abs/2305.15167 🌟 🌟

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