Massive effort from amazing collaborators @allardmaxime079 @MFlageat and @CULLYAntoine. Super thankful for the opportunity and privilege to play a part in this work!
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Bryan Lim
74 posts
Bryan Lim
@bryanlimwt
PhD Student @imperialcollege. AI/ML/Robotics.
Katılım Şubat 2021
246 Takip Edilen964 Takipçiler
Super happy to share that our work on robot adaptation is now out in @NatureComms!
Imagine a robot being paralysed in some areas from unknown failures like a faulty or damaged wheel or motor, operating and driving such a vehicle is near impossible.
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Maxime Allard@allardmaxime079
🤖Thrilled to share that robotics work from my PhD is out in @NatureComms 🎉 "Getting robots back on track by reconstituting control in unexpected situations with online learning" With @MFlageat , @bryanlimwt , @CULLYAntoine @imperialcollege 🧵below
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Almost exactly 10 years after joining @imperialcollege as a Postdoc, I am honoured to announce that I am now Professor in Machine Learning and Robotics! 👨🎓 🤖
My fantastic team found the best gift to celebrate this special occasion!
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Thanks a lot, Ed!!! It is definitely an award for the whole lab! 🦾
Edward Johns@Ed__Johns
I was a proud PhD supervisor today - Vitalis Vosylius (@vitalisvos19) won the Amazon PhD Prize at Imperial College! @ImperialRobots He gave the judges a live demo of Instant Policy (tinyurl.com/yf6xjxet), whilst we were watching on the TV down the corridor. Congrats Vitalis!
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More information in this 🧵 too!
x.com/bryanlimwt/sta…
Bryan Lim@bryanlimwt
💡⚙️ Ideas and inventions are rarely generated and created in isolation 🏝️ We explore using few/many-shot prompting of language models with quality-diverse examples provided from QD algorithms for solution generation for QD problems! Work done with @MFlageat @CULLYAntoine
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Had a great time at @ALifeConf this week presenting In-context Quality-Diversity! Feel free to reach out if any of this is interesting #ALIFE2024
Hiroki Sayama@HirokiSayama
Bryan Lim discusses LLMs as an in-context quality-diversity generator #ALIFE2024 @ALifeConf
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Compared to other QD algorithms which use a few solutions from the archive for the next offspring (i.e. parents for a mutation/crossover or the init of an ES mean dist.), In-context QD makes greater use of the quality-diverse solutions in the archive for solution generation
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💡⚙️ Ideas and inventions are rarely generated and created in isolation 🏝️
We explore using few/many-shot prompting of language models with quality-diverse examples provided from QD algorithms for solution generation for QD problems!
Work done with @MFlageat @CULLYAntoine
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Excited to be presenting this year’s edition of Evolutionary Reinforcement Learning (EvoRL) @GeccoConf 🦎🦾 with @MFlageat @CULLYAntoine, which will be a tutorial instead of a workshop!
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Very happy to share that I passed my PhD viva yesterday! Extremely grateful to @CULLYAntoine who has been a great advisor and mentor throughout this journey. Thank you for giving me this opportunity of a lifetime!
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@bryanlimwt @CULLYAntoine Congratulations Bryan!!! Excited to see what else you do
Adding to your fun fact, Antoine went through C++ code with me line by line when I first joined
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