RobotLearn Research Team @ Inria Grenoble retweetledi
Last Early Bird spots available (Dec 23rd) to hear Prof. Magalie Ochs' keynote at SoRAIM. Check project.inria.fr/soraim/
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RobotLearn Research Team @ Inria Grenoble
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RobotLearn Research Team @ Inria Grenoble
@RobotLearnInria
RobotLearn is a research team at Inria Grenoble, created on July 1st, 2021. We aim to contribute to the development of robotic social intelligence.
Grenoble, France Katılım Temmuz 2021
106 Takip Edilen146 Takipçiler
RobotLearn Research Team @ Inria Grenoble retweetledi
Doing a PhD/postdoc in computer vision or NLP? Interested in multimodal conversational AI and social robotics? Register now for SoRAIM 2026, a unique opportunity to delve into SoTA research across all these disciplines, with inspiring keynote speakers and hands-on sessions.
SoRAIM Winter School@soraim_comlearn
What a speaker line up! Register (project.inria.fr/soraim/) if you want to hear these wonderful people.
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RobotLearn Research Team @ Inria Grenoble retweetledi
Hey there! We are organising a wonderful Winter School in the French Alps! Check it out!!!
with @thomashueber @Steph_lat Olivier Perrotin and Laurent Girin, supported by @inria_grenoble @GipsaLab @CNRS @UGrenobleAlpes @MIAI_UGA @PALRobotics @gdr_tal_cnrs @RobotLearnInria
SoRAIM Winter School@soraim_comlearn
What a speaker line up! Register (project.inria.fr/soraim/) if you want to hear these wonderful people.
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RobotLearn Research Team @ Inria Grenoble retweetledi
[#PhD 👩🎓]
Félicitations à Xiaoyu Lin (équipe @RobotLearnInria) qui a soutenu sa thèse "Modèles génératifs à variables latentes profondes pour le traitement multimédia" #deeplearning 🤖
➕ d'infos :
theses.fr/s256317
inria.fr/fr/robotlearn
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PhD Position Open in Deep Information Geometry.
At the RobotLearn team, and together with @plc_rodrigues from @InriaStatify and @xavirema we are looking for a PhD candidate motivated to explore deep information geometry. Please apply following the link below.
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Open internship position at our team on "Social Robotics with ChatGPT". Check: team.inria.fr/robotlearn/mas…
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Open intership position at our team on "Deep Statistical Manifolds". Check: team.inria.fr/robotlearn/mas…
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Are you working on RL in the Grenoble-Lyon area? This might be interesting: team.inria.fr/robotlearn/rl-… #reinforcementlearning #rl @inria_grenoble @MIAI_UGA
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Màster internship proposal in our team at @inria_grenoble!
Chris Reinke@ScienceReinke
Master Internship about Automated Discovery of Moving Lifeforms in Celluar Automata (#Lenia) using #DeepLearning. At @RobotLearnInria. Start: Beginning of 2023 Duration: 5 - 6 months Learn more at: team.inria.fr/robotlearn/job…
Català
Si vous voulez en savoir plus à propos du projet @SpringH2020 et de comment les robots socialement intelligents peuvent être appliqués à la gérontologie, c'est par ici :
Centre Inria de l'Université Grenoble Alpes@inria_grenoble
C'est la semaine de l' #Europe 🇪🇺 ! Pour l'occasion (re)découvrez notre article sur @SpringH2020 : un projet multidisciplinaire et européen sur la robotique sociale🤖 Avec @xavirema et @RobotLearnInria ➡ inria.fr/fr/spring-robo…
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RobotLearn Research Team @ Inria Grenoble retweetledi
Only 10 days left to apply to this assistant/associate professor position in our team!
Stéphane LATHUILIÈRE@Steph_lat
Associate/assistant professor (maitre de conf) position to work on Learning for Video Processing and Computer Vision at @telecomparis @IP_Paris_. Details available at: institutminestelecom.recruitee.com/l/en/o/assista….
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Finally, we looked into adapting self-supervised methods to the continual learning setting, by adding a predictor that maps previous features into the new feature space. arxiv.org/abs/2112.04215
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Second, we investigated the use of self-supervised method for sound source localisation in videos.
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We are very happy to announce that the RobotLearn team has three papers accepted at CVPR 2022! Congratulations to the PhD students @GUO_Wen_, @BieXiaoyu, Hanyu Xuan, @DonkeyShot21, and @victorturrisi, and to our collaborators @fmorenoguer @eliricci_ @inthebrownbag @julienmairal.
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Following our trend on using dynamic variational autoencoders, we propose an unsupervised speech enhancement algorithm based on #dvae. @BieXiaoyu @SimonLeglaive @xavirema and Laurent Girin. @inria_grenoble @UGrenobleAlpes @MIAI_UGA @SpringH2020
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We hope 2022 is going to be as fruitful as the now gone 2021. Keep posted!
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We have also contributed to the use of neural episodic control in combination with linear successor features (team.inria.fr/robotlearn/suc…).
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Happy new year to everyone from the RobotLearn team. Over the past year, we have achieved several contributions that we would like to summarise. #teamwork @MIAI_UGA @inria_grenoble @UGrenobleAlpes @SpringH2020
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