Frederik Boe Hüttel

18 posts

Frederik Boe Hüttel

@FBoeHuttel

Ph.D. student @ Machine Learning for Smart Mobility @mlsm_dtu @DTUtweet

Katılım Mart 2014

199 Takip Edilen56 Takipçiler

Frederik Boe Hüttel retweetledi

Thea Brüsch@thea_brusch·10 May

Exciting stuff happening tomorrow at the Re-Align workshop ☀️☀️

Lenka Tětková@LenkaTetkova

See our #poster "On convex decision regions in deep network representations" tomorrow at the #Workshop on #RepresentationalAlignment at @iclr_conf arxiv.org/abs/2305.17154. @thea_brusch @tsalstroem @TeresaScheidt @jonafold @Tweetteresearch @DTUtweet @DTU_Compute #XAI #AIAlignment

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DTU Machine Learning for Smart Mobility@mlsm_dtu·26 Nis

#JobAlert📣We are #recruiting a #PhD in #ReinforcementLearning for Intelligent #Traffic Signal Control! Don't hesitate to apply, share with interested candidates, or contact us if you have questions 😊 #phdpositions #phdopportunity #HIRINGNOW efzu.fa.em2.oraclecloud.com/hcmUI/Candidat…

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DTU Machine Learning for Smart Mobility@mlsm_dtu·18 Oca

Last week, our group presented/co-authored 4 papers at #TRB2023, in Washington D.C. Check out below for more details including links to the papers! #TRBAM #MachineLearning #Transportation #Mobility mlsm.man.dtu.dk/mlsm-group-at-…

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DTU Machine Learning for Smart Mobility@mlsm_dtu·16 Oca

During #TRB2023 @FBoeHuttel presented his work "Mind the Gap – Difference Between Censored and Uncensored Electric Vehicle Charging Demand" Co-authors: @fmpr87 and @camara421 #TRBAM @NASEMTRB #MachineLearning

DTU Machine Learning for Smart Mobility tweet media

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DTU Machine Learning for Smart Mobility@mlsm_dtu·10 Oca

Another talk by Christopher Riis on 'Using #ComputerVision to Register Patterns of #Bicycle Helmet Use' at #trb2023 #TRBAM #TRBAM2023 #TRB @NASEMTRB #MachineLearning #Transportation #cycling

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Frederik Boe Hüttel@FBoeHuttel·6 Oca

Hit me up if you to chat!

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Frederik Boe Hüttel@FBoeHuttel·6 Oca

I'm at #TRBAM this week! Im presenting some work on EV demand modelling.

DTU Machine Learning for Smart Mobility@mlsm_dtu

Our group will be next week at the #Transportation Research Board Annual Meeting #TRB2023 @NASEMTRB to present 3 papers and a talk on 'using #computervision to register patterns of #bicycle helmet use'. Join us if you are in D.C! Details in the link below: mlsm.man.dtu.dk/mlsm-group-at-…

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Frederik Boe Hüttel@FBoeHuttel·16 Ara

@Tea_Pearce Awesome work! It was a pleasure to read and meet you at NeurIPS. Here is a similar paper from the transport domain😀. ieeexplore.ieee.org/document/98470…

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Tim Pearce@Tea_Pearce·15 Ara

1/ Interested in neural networks, survival analysis, and quantile regression? This paper is for you. 😁 As presented at #NeurIPS2022. Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis Paper: arxiv.org/abs/2205.13496

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Daniele Gammelli@DanieleGammelli·8 Ara

Can we learn efficient algorithms to solve classical optimization problems over graphs? In our recent @LogConference paper, we propose graph reinforcement learning as a general framework to solve network control problems! 📜 openreview.net/forum?id=1sPcf… 🧵👇 (1/n)

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DTU Machine Learning for Smart Mobility@mlsm_dtu·1 Ara

Christoffer Riis and @FBoeHuttel presenting their paper "Bayesian Active Learning with Fully Bayesian Gaussian Processes" at #NeurIPS2022😊 You can find the paper and the code here: mlsm.man.dtu.dk/mlsm-at-neurip…

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Frederik Boe Hüttel retweetledi

DTU Machine Learning for Smart Mobility@mlsm_dtu·29 Kas

Co-authors: Francisco Antunes, @camilimaz, @camara421

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Frederik@FrederikWarburg·26 Eyl

#Visuallocalization is crucial for many robotics applications! However, extreme viewpoint changes still challenge current methods. Next month at #IROS2020 #RAL, we present an aerial to street-level dataset to study visual localization under extreme viewpoint changes.

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Frederik Boe Hüttel retweetledi

DTU Machine Learning for Smart Mobility@mlsm_dtu·20 Eyl

Our team is ready for Fall 2022! We also launched our LinkedIn page (linkedin.com/company/machin…) so don't forget to follow us there too where we will be sharing more news about our research work! #MachineLearning #Mobility @dtumanagement

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Frederik@FrederikWarburg·16 Eyl

#Uncertainties should be deduced - not learned! In our #Neurips2022 📰, we develop a (1) post-hoc Laplacian autoencoder with good latent uncertainties, (2) an online training procedure that improves the output variance, and (3) a hessian approximation that scales to large images!

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Frederik@FrederikWarburg·7 Eyl

Autonomous vehicles will disrupt our society, but how do they work? What are the technological and ethical challenges? I got the opportunity to discuss these topics in the new Danish podcast series on #AI. Listen to “Spøgelset i maskinen” (in Danish) here: tinyurl.com/mr3yp562

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Frederik Boe Hüttel@FBoeHuttel·31 Ağu

I'm coming home! 🇩🇰🇩🇰🇩🇰 The last 6 months just flew by me - with plenty of new friends, impressions, and experiences! It was my pleasure to experience @MIT 's magic. I'm also looking forward to returning to the @mlsm_dtu to continue my Ph.D. studies. #MachineLearning

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Frederik Boe Hüttel retweetledi

DTU Machine Learning for Smart Mobility@mlsm_dtu·29 Ağu

Last week, our group presented 4 papers at #trafikdage in Aalborg, Denmark. In addition, @camara421 organized a session about #AI in modelling and management traffic! Check out below for more details including the slides/papers. mlsm.man.dtu.dk/mlsm-group-at-…

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Frederik Boe Hüttel retweetledi

DTU Machine Learning for Smart Mobility@mlsm_dtu·23 Ağu

And that's a wrap! Our last talk at #trafikdage was about feasibility of detecting cyclists’ phone use with #ComputerVision by Christoffer Riis! Co-authors: @felix_w_s, Jakob Kristensen, Oguzhan Gül, Kira Hyldekær Janstrup, Hanhe Lin, @camara421, and Frederik Boe Hüttel

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Keşfet

@fmpr87 @NASEMTRB @Tea_Pearce @LogConference @camilimaz @dtumanagement @MIT @mlsm_dtu