Sebastian Weichwald (@sweichwald) profile picture

Why? Causality, Statistics, Machine Learning, Interdisciplinarity @ @science_ku @UCPH_Research formerly @MPI_IS & @ETH_en

EU
Joined June 2016
Photo by Sebastian Weichwald (@sweichwald)Photo by Sebastian Weichwald (@sweichwald)Photo by Sebastian Weichwald (@sweichwald)Photo by Sebastian Weichwald (@sweichwald)Photo by Sebastian Weichwald (@sweichwald)Photo by Sebastian Weichwald (@sweichwald)Photo by Sebastian Weichwald (@sweichwald)Photo by Sebastian Weichwald (@sweichwald)Photo by Sebastian Weichwald (@sweichwald)Photo by Sebastian Weichwald (@sweichwald)
What is a causal model and how is it different from a "common" statistical model? πŸ‘‡ Thread on a mental picture and intuition how one may think about (a subclass of) causal models and the causal discovery problem. 1/ @bttyeo @eliasbareinboim @KordingLab @EpiEllie @causalinf
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What is causal about causal models and representations?. arxiv.org/abs/2501.19335
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πŸ“’ PhD opportunities at the University of Copenhagen in Statistics and Insurance/Economics Maths employment.ku.dk/phd?show=16… (apply by April 1) and in Denmark more broadly Danish Data Science Academy Fellowship ddsa.dk/phdfellowshipcall202… (apply by March 5)
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Sebastian Weichwald retweeted
πŸ“’ Open Positions in Stats @ University of Copenhagen math.ku.dk/english/about/job… Very liveable city, kind & helpful colleagues, excellent environment w/ vibrant community – can only recommend and happy to answer questions via email ;-) Spread the word and apply by OCT 6‼️
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πŸ“’ Open Positions in Stats @ University of Copenhagen math.ku.dk/english/about/job… Very liveable city, kind & helpful colleagues, excellent environment w/ vibrant community – can only recommend and happy to answer questions via email ;-) Spread the word and apply by OCT 6‼️
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Sebastian Weichwald retweeted
Adjustment Identification Distance: A gadjid for Causal Structure Learning ift.tt/jF71ZDt
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Sebastian Weichwald retweeted
πŸ“’ here's a new πšπšŠπšπš“πš’πš for Causal Structure Learning: 𝐆raph 𝐀𝐃𝐉ustment 𝐈dentification 𝐃istances to compare DAGs or CPDAGs (!) in terms of the identifying formulas they suggest for causal effects. πŸ’» Try it: pip install gadjid πŸ“š Read it: doi.org/10.48550/arXiv.2402.… 1/
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Sebastian Weichwald retweeted
πŸ“’ PhD positions in causality/statistics/ML in Copenhagen math.ku.dk/english/about/job… β†’ beyond the named projects, several independent stipends are available – just apply with your project ideas and supervisor suggestion πŸ’­ aicentre.dk/phd-openings Apply by April 1st πŸ“¨
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πŸ“’ PhD positions in causality/statistics/ML in Copenhagen math.ku.dk/english/about/job… β†’ beyond the named projects, several independent stipends are available – just apply with your project ideas and supervisor suggestion πŸ’­ aicentre.dk/phd-openings Apply by April 1st πŸ“¨
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Sebastian Weichwald retweeted
The Pioneer Centre for AI invites applications for 9 PhD Positions for different projects at the Centre across our collaboratories and partner universities. πŸ—“ Application deadline is 22 March and 1 April, 2024. For more information: aicentre.dk/phd-openings
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πŸ“’ here's a new πšπšŠπšπš“πš’πš for Causal Structure Learning: 𝐆raph 𝐀𝐃𝐉ustment 𝐈dentification 𝐃istances to compare DAGs or CPDAGs (!) in terms of the identifying formulas they suggest for causal effects. πŸ’» Try it: pip install gadjid πŸ“š Read it: doi.org/10.48550/arXiv.2402.… 1/
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Why? We need 𝒄𝒂𝒖𝒔𝒂𝒍 performance metrics to guide the development of 𝒄𝒂𝒖𝒔𝒂𝒍 structure learning algorithms. Existing graph distances are non-causal, ignore causal order, or slow 🐌 We develop new algorithms for the too fast πŸš΄β€β™€οΈ and too causal Ancestor- and Oset-AID 2/
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Using Neuro-Symbolic AI can boost the prediction accuracy... but are you learning the right concepts? πŸ€– The answer is very tricky, but it is "no" in general 😱 Introducing our latest paper, accepted at #NeurIPS2023! With @tetraduzione, @andrea_whatever, and @looselycorrect.
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Introducing our #NeurIPS2023 paper: "Causal Component Analysis" (CauCA) – a causal generalization of Independent Component Analysis (ICA), and a special case of Causal Representation Learning (CRL). 1/10 πŸ“: arxiv.org/abs/2305.17225 πŸ’»: github.com/akekic/causal-com…
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what does "alignment" mean these days in #AI and #ML? in a nutshell, that big tech has a clear agenda and we shall align with it. states and governments are doing this right now (and they influence academia in a weird feedback)
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'Bike riders recognise that mandatory helmet legalisation does not tackle the risk of injury at its root [and] felt that helmets dehumanise bike riders which could lead to further violence against them.' 🚨NEW STUDY🚨: sciencedirect.com/science/ar… (cartoon by @davewalker)
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Sebastian Weichwald retweeted
On Friday, 20 Oct., I will give a talk at the University of Copenhagen. I will present work on identifiable representation learning---independent influences, multiple views & Causal Component Analysis Date/Time: 20 Oct. 2023, 11:15 Place: Aud 10, Universitetsparken 5, HCØ
Into identifiability and causal representation learning and close to Copenhagen? πŸ‘‡ πŸ“’ @luigigres is visiting Copenhagen Causality Lab 🀩 πŸ“… Talk: Oct 20, 11:15 math.ku.dk/english/calendar/… πŸ‘₯ get in touch, if you want to meet with Luigi Oct 19/20 @AiCentreDK @MLSectionUCPH @CogSys
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How (not) to solve a bottleneck. (Original from 'Movement': blackwells.co.uk/bookshop/pr…. Enhanced by @Jtrace_a_stras)
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Sebastian Weichwald retweeted
Into identifiability and causal representation learning and close to Copenhagen? πŸ‘‡ πŸ“’ @luigigres is visiting Copenhagen Causality Lab 🀩 πŸ“… Talk: Oct 20, 11:15 math.ku.dk/english/calendar/… πŸ‘₯ get in touch, if you want to meet with Luigi Oct 19/20 @AiCentreDK @MLSectionUCPH @CogSys
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