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Category Archives: news
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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2020 Retrospective
What a year this was...! This retrospective though, won't be about the unprecedented situation that we all went through. We'll take some time to revisit the highlights of our group's activities throughout this year. Let's go!
Papers in NeurIPS 2020
We are very happy to announce that the members of our team have had two accepted papers in NeurIPS 2020!
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Tagged Alexandros Kalousis, Amina, Amina Mollaysa, internships, Jason, Jason Ramapuram, NeurIPS, NIPS, NIPS conference, papers
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Welcome to Naoya
We have the pleasure to welcome Naoya Takeishi as a new postdoc into our team. His expertise and experience with integrating the theoretical understanding of physical systems into machine learning as well as with data-driven analysis of nonlinear dynamical systems is a strong contribution to our research portfolio and we are looking forward to inspiring and enriching discussions and collaborations. Naoya will also reinforce our team in the industrial project IAI: Industrial Artificial Intelligence for intelligent machines and manufacturing digitalization. In addition to all the science he is about to immerse to, we wish he enjoys his stay with us and in Geneva, Switzerland and we hope to learn from him a little more about Japan and its culture. ようこそ!
Statistical Learning Workshop – Tentative program available
The tentative program of the Statistical Learning Workshop, which takes place on-line the whole day of the 18th of September, is now available on the workshop's site http://dmml.ch/statistical-learning-workshop/!
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Tagged invited talk, machine learning, phd student, presentation, statistical learning, Talk, workshop
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