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Category Archives: news
New Journal Paper in Sensors MDPI
Our latest paper: “Can I Trust This Location Estimate? Reproducibly Benchmarking the Methods of Dynamic Accuracy Estimation of Localization”. has been published in the Journal Sensors by MDPI. This work reviews the relevant literature related to the accuracy estimation of indoor positioning … Continue reading
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Tagged Alexandros Kalousis, eratosthenes, Grigorios G. Anagostopoulos, IoT positioning, localization, LoRaWAN, LoRaWAN positioning, outdoor localization, Outdoor positioning, paper, positioning, snsf
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2021 Retrospective
As we approach the Christmas period, and holidays are ahead of us, we seize the opportunity and take a moment to reflect on the year that is about to be completed. Let's go!
PhD Thesis defense of Lionel Blondé
Lionel Blondé will defend on Tuesday the 21st of December 2021 at 15:00 his PhD thesis entitled: "Counterfactual Interactive Learning: Designing Proactive Artificial Agents that Learn from the Mistakes of other Decision Makers" Due to the health measures currently in … Continue reading
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Tagged Alexandros Kalousis, deep leaning, generative modeling, Lionel, Lionel Blonde, phd, PhD Thesis, presentation, VAE
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Two Papers Presented in IPIN 2021
Attending a conference in a presential mode, after two years of online events, can be quite a thrill!At the end of November 2021, Greg the pleasure to attend the 11th Indoor Positioning and Indoor Navigation (IPIN 2021) International Conference , … Continue reading
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Tagged eratosthenes, generative modeling, Greg, Grigorios G. Anagostopoulos, IPIN, IPIN conference, localization, outdoor localization, paper, papers, positioning, reproducibility
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PhD Thesis defense of Jason Ramapuram
Jason Ramapuram will defend on Wednesday the 15th of September 2021 at 13:00 his PhD thesis entitled: "Finding signals in the void: Improving deep latent variable generative models via supervisory signals present within data." co-directed by Prof. Stephane Marchand-Maillet and … Continue reading
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Tagged Alexandros Kalousis, deep leaning, generative modeling, Jason, Jason Ramapuram, Kanerva++, phd, PhD Thesis, presentation, VAE, Variational saccading
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Best student paper award by Joao Ramos in ECML/PKDD 2021
It is our pleasure to announce that Joao Ramos received the best student data mining paper award in ECML/PKDD 2021 for the work he did in modelling pathological gait to eventually support treatment planning. Joao's work takes place in the … Continue reading
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Tagged Alexandros Kalousis, award, best paper award, conference, ECML/PKDD conference, graph network, Joao, Lionel Blonde, paper, SimGait, snsf, VAE
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Departure of Magda Gregorova for a Professorship in Germany
After eight amazing years, one PhD acquired, the co-initiation of a new Master's program for HEG, several published papers, endless fruitful discussions in team meetings and numerous initiations of fun team activities, Dr. Magda Gregorova is departing from our group. … Continue reading
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Special session in IPIN2021
We are happy to announce that Greg is organising the Special Session "Data Compression, Data Augmentation and Generative Modeling in Indoor Positioning" in the upcoming Indoor Positioning and Indoor Navigation Conference (IPIN2021).
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Tagged generative modeling, Greg, Grigorios G. Anagostopoulos, IPIN, IPIN conference, localization, paper, papers, positioning
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Kanerva++ at ICLR21
The ICLR21 conference is still a few weeks away but to wet your appetite already, we are glad to let you know that Jason Ramapuram will be presenting there his new paper Kanerva++: Extending the Kanerva Machine With Differentiable, Locally Block Allocated Latent Memory. The paper is a result of a successful collaboration with Yan Wu from Deepmind.
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Tagged conference, ICLR, Jason, Jason Ramapuram, Kanerva++, paper
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PhD Thesis defense of Amina Mollaysa
Amina Mollaysa will defend her PhD Thesis entitled "Structural and Functional Regularization of Deep Learning Models" on Friday 26/02/2021, at 15h00 CET. If you are interested in attending the PhD defence of Amina Mollaysa, please send an email with the title "Thesis defense Mollaysa - Zoom" to alexandros.kalousis@hesge.ch to receive the Zoom link.
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Tagged Amina, Amina Mollaysa, deep leaning, generative modeling, phd, phd in machine learning, Thesis, VAE
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