Sarah Perrin (@sarah_perrin_) 's Twitter Profile
Sarah Perrin

@sarah_perrin_

Research Scientist @GoogleDeepMind. Reinforcement Learning, Mean Field Games & Game theory

ID: 1008883085339848704

calendar_today19-06-2018 01:24:06

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Sarah Perrin (@sarah_perrin_) 's Twitter Profile Photo

I'll be presenting an overview of learning Mean Field Games and Mean Field Control with Reinforcement Learning next Tuesday 👀

Sarah Perrin (@sarah_perrin_) 's Twitter Profile Photo

Very happy to co-organize the Gamification and Multiagent Solution workshop at ICLR 2025 2022! We are accepting papers, more infos on our website. --> gamificationmas.com

Olivier Bachem (@olivierbachem) 's Twitter Profile Photo

This work was led by Matthieu Geist in a collaboration between Google AI, @Deepmind, and Inria. It is joint work between Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, myself, Rémi Munos, and Olivier Pietquin.

Gamification and Multiagent Solutions Workshop (@gamificationmas) 's Twitter Profile Photo

🏅💸💰 AWARD ALERT 💰💸🏅 The Cooperative AI Foundation (CAIF) kindly offered to give 2 awards of 500$ each for “Best Cooperative AI paper” and “Best Cooperative AI poster”! We are very grateful and waiting for your submissions 😎 cooperativeai.com/foundation

Scool (@inriascool) 's Twitter Profile Photo

Today at 6PM CET, Sarah Perrin is going to present her work on learning master policies that leverage generalisation properties of mean-field games. A master policy leads to a Nash equilibrium irrespective of the initial distribution. Visit us at R3B for more! 🙏 #AAAI2022

Today at 6PM CET, <a href="/sarah_perrin_/">Sarah Perrin</a> is going to present her work on learning master policies that leverage generalisation properties of mean-field games. A master policy leads to a Nash equilibrium irrespective of the initial distribution. Visit us at R3B for more! 🙏 #AAAI2022
Sarah Perrin (@sarah_perrin_) 's Twitter Profile Photo

First paper accepted ICML Conference! And this means... first in-person conference 🥳 --> "Scalable Deep Reinforcement Learning Algorithms for Mean Field Games" arxiv.org/abs/2203.11973

Scool (@inriascool) 's Twitter Profile Photo

Today, our PhD student Sarah Perrin is going to give an invited talk at #EWRL2022 in Milan. At 9 AM, she will talk about "Scaling up MARL with MFGs and vice versa". Stay tuned to know more of Scool's presence at #EWRL2022. 😃🙏

Sundar Pichai (@sundarpichai) 's Twitter Profile Photo

Introducing Gemini 1.0, our most capable and general AI model yet. Built natively to be multimodal, it’s the first step in our Gemini-era of models. Gemini is optimized in three sizes - Ultra, Pro, and Nano Gemini Ultra’s performance exceeds current state-of-the-art results on

Introducing Gemini 1.0, our most capable and general AI model yet. Built natively to be multimodal, it’s the first step in our Gemini-era of models. Gemini is optimized in three sizes - Ultra, Pro, and Nano

Gemini Ultra’s performance exceeds current state-of-the-art results on
Geoffrey Cideron (@cdrgeo) 's Twitter Profile Photo

Happy to introduce our paper MusicRL, the first music generation system finetuned with human preferences. Paper link: arxiv.org/abs/2402.04229

Jeff Dean (@🏡) (@jeffdean) 's Twitter Profile Photo

Introducing Gemma - a family of lightweight, state-of-the-art open models for their class, built from the same research & technology used to create the Gemini models. Blog post: blog.google/technology/dev… Tech report: goo.gle/GemmaReport This thread explores some of the

Introducing Gemma - a family of lightweight, state-of-the-art open models for their class, built from the same research &amp; technology used to create the Gemini models.

Blog post:
blog.google/technology/dev…
Tech report:
goo.gle/GemmaReport

This thread explores some of the
Armand Joulin (@armandjoulin) 's Twitter Profile Photo

Are small models still undertrained? We are releasing a 2B model that beats GPT-3.5. The crazy part is that it was distill on only 2T tokens from a small model. Distillation is the future of LLMs with the growing availability of large and efficient open models!

Are small models still undertrained? 
We are releasing a 2B model that beats GPT-3.5. The crazy part is that it was distill on only 2T tokens from a small model. 
Distillation is the future of LLMs with the growing availability of large and efficient open models!