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Our group's website is now online! Make sure to check it! mlsm.man.dtu.dk

Check out the 11 contributions involving DTU Machine Learning for Smart Mobility members at TRB2019! #TRb2019 #TRB19 #TRBAM mlsm.man.dtu.dk/mlsm-group-at-…

Congratulations to Ioulia Markou for the her PhD dissertation!!! #congrats #throwyourhats #MLSM DTU Management

One more step towards future traffic control: check our latest paper on the impact of demand surges, incidents and sensor failures on deep reinforcement learning-based traffic signal control arxiv.org/abs/1904.08353 #MachineLearning #trafficcontrol #arXiv

New PhD student position open at the Machine Learning for Smart Mobility group DTU Machine Learning for Smart Mobility from the Technical University of Denmark on "Machine Learning for shared, connected and cooperative automated vehicles" dtu.dk/english/about/…

Quite productive visit to #kobecity with 6 papers and a session with the latest developments on machine learning and discrete choice modelling at #ICMC #japan icmconference.org.uk/index.php/icmc…

"The paradigm shift that we believe is ideal for us as a society is where the transport system primarily adapts to us," says prof Francisco Pereira DTU Management. Meet him at DTU HighTech Summit. Sign up here👉 hightechsummit.dk #dkforsk #dktrp #dkdigi #HighTechDTU

Our members Inon Peled & Filipe Rodrigues just presented the latest research on reinforcement learning for non-recurrent traffic control & uncertainty estimation in demand prediction for autonomous mobility at #IEEE #itsc2019 NZ its.papercept.net/conferences/co…. Great growing community IEEE Intelligent Transportation Systems Society

Our team is ready to start the 2020 season🏃‍♀️🏃‍♂️

New PhD student position open at the Machine Learning for Smart Mobility group (mlsm.man.dtu.dk) from the Technical University of Denmark: dtu.dk/english/About/…

How can we learn *transferrable* control policies for Autonomous Mobility-on-Demand systems across cities? Our recent work shows how graph neural networks and deep RL agents exhibit promising zero-shot transfer capabilities. Up on arXiv! arxiv.org/abs/2104.11434

Cool work from our PhD student Daniele Gammelli on graph neural network reinforcement learning for autonomous mobility-on-demand systems in collaboration with Stanford ASL!

Join us at #INNF Workshop #ICML2021 at 11am UTC (9am CET) today! The efficiency of mobility systems depends on the ability to model the need for transportation. We show how LVMs and normalizing flows enable us to generate distributions matching complex urban topologies.

My paper on "Scaling Bayesian inference of mixed multinomial logit models to large datasets" is now published online: sciencedirect.com/science/articl… Make sure to check out the provided PyTorch implementation with an easy-to-use interface: github.com/fmpr/amortized…

Is a complex deep neural network better than a simple linear regression for spatio-temporal forecasting in transportation problems? Check here how a simple linear regression can provide comparable results to many state-of-the-art approaches: arxiv.org/abs/2203.02954

Predictions from ML models are often used for downstream decision-making tasks, where a sequential predict-then-optimize strategy is used to train the ML model. But do accurate predictions translate into better decisions? Spoiler: NO arXiv: arxiv.org/abs/2108.00858 🧵(1/5)

The 7th International Choice Modelling Conference (ICMC) will be held in Reykjavik, Iceland from 23-25 May 2022. Our group will contribute with six interesting papers. Check out below for more details. mlsm.man.dtu.dk/mlsm-group-at-… #MachineLearning #ICMC #ChoiceModelling #Transport

#JobAlert Our DTU Machine Learning for Smart Mobility group is recruiting 3 #PhDposition in exciting topics!! Take a look and apply ! 1) lnkd.in/eqQuiJT7 2) lnkd.in/eZxybAxU 3) lnkd.in/ersgsBZA #MachineLearning #publictransport #simulation #behaviour #traffic #autonomousdriving

Congrats to Daniele Gammelli whom successfully defended his #PhD thesis "Learning and Control for Adaptive Transportation Systems". You will be missed! Check below for more info including the abstract and the list of 6 papers published by Daniele! mlsm.man.dtu.dk/new-ph-d-gradu…

Check out our new AAAI 2018 paper: "Deep Learning from Crowds" (arxiv.org/abs/1709.01779). Something to consider the next time you train a deep NN on crowdsourced labels...