Pascal Leroy

PhD @UniversiteLiege - Interested in Multi-agent RL

[Pascal Leroy @PaLeroy]

We released IMP-MARL: a Suite of Environments for Large-scale
Infrastructure Management Planning via MARL.
In IMP-MARL, agents decide the inspections and repairs needed to limit the risk of system failure, based on the probability distributions of damage.
https://t.co/Qqrztqh3r4

[Pascal Leroy @PaLeroy]

Interesting to link asymmetric learning and CTDE in MARL!

[Gaspard Lambrechts @GsprdLambrechts]

📝 "A Theoretical Justification for Asymmetric Actor-Critic Algorithms" was accepted at #ICML!

Never heard of asymmetric actor-critic algorithms? Yet, many successful #RL applications use them.

But these algorithms are not fully understood. Below, we provide some insights.

[Gaspard Lambrechts @GsprdLambrechts]

📝 "A Theoretical Justification for Asymmetric Actor-Critic Algorithms" was accepted at #ICML!

Never heard of asymmetric actor-critic algorithms? Yet, many successful #RL applications use them.

But these algorithms are not fully understood. Below, we provide some insights.

[Damien ERNST @DamienERNST1]

[Thanks for sharing] Dear all, my university is opening a call to give two-year positions for post-docs. If you are willing to join my group to work for example on energy systems, AI for defense, LLMs for the industry or reinforcement learning (all the things in which I am interested :) ), please do not hesitate to contact me.

[Damien ERNST @DamienERNST1]

[Thanks for sharing] We will have the immense pleasure to welcome the fantastic researcher @FlorianFelten1 for a research talk on Multi-Objective Reinforcement Learning in my research unit this Friday.

Please do not hesitate to come!

More information: https://t.co/vIipH7ZzdX

[Pascal Leroy @PaLeroy]

@FrancoisRozet Well done!

[François Rozet @FrancoisRozet]

📢 Are you interested in diffusion models and inverse problems? Check out our new preprint "Learning Diffusion Priors from Observations by Expectation Maximization" with @g4ndry, François Lanusse and @glouppe! 🧵

https://t.co/2k33Lcjdb6

[Gaspard Lambrechts @GsprdLambrechts]

📝 New paper "Parallelizing Autoregressive Generation with Variational State Space Models".

It is an SSM-based sequence model that generates in //, while remaining recurrent.

We will present it at the #ICML2024 workshop on the Next Generation of Sequence Modeling Architectures.

[Damien ERNST @DamienERNST1]

• Let us call him now Dr @PaLeroy, my 18th PhD student to graduate. 

• He successfully defended his PhD thesis related to multi-agent reinforcement learning. 

• His excellent manuscript can be downloaded here:
https://t.co/DbdHkQHeA5

#reinforcementLearning #artificialIntelligence

[Gilles Louppe @glouppe]

The position is still open! 👇

[Rupali Bhati @BhatiRupali]

Checkout this new workshop on coordination and cooperation in #MARL.

[Gilles Louppe @glouppe]

📢 Open PhD position in my group, on simulation-based inference and generative models for particle physics, on a joint project with Fabio Maltoni and Tilman Plehn https://t.co/8lbormpTas

[Damien ERNST @DamienERNST1]

[Thansk for sharing].

We are hiring new people for developing and using our tool GBOML for the planification of complex  energy systems.

Here is the link to the job offer:
https://t.co/iRFxDJucxs

#energyTransition  #optimisation #machineLearning

[Stefano V. Albrecht @s_albrecht]

Our Multi-Agent RL framework EPyMARL, which extends the original PyMARL framework of @whi_rl, is widely used in MARL research (nearly 400 stars on Github!) and several MARL benchmarks have been built on it. We list three in this thread!
Blog: https://t.co/AO24ZzFrPw
(1/4)

[Haitham Bou Ammar @hbouammar]

In this episode of Mate with a Fantastic Researcher, @AdrienBolland from @DamienERNST1 takes us on a journey to explore reinforcement learning. He defines a set of criteria for when intrinsic and entropy-based RL works. He analyses them in a simple set of experiments to convey deep insights into the process of exploration in #RL.

This is one of the most profound and well-executed analysis papers I have seen in a while! It is really awesome to see that some teams are still caring for fundamentals beyond the hype!

Don't miss the episode: https://t.co/zLjxlUvwi2

Cheers to getting away from the philosophical hype :P

#AI #MachineLearning

[Pascal Leroy @PaLeroy]

@EugeneVinitsky @SimonPrinceAI Agreed!
I read the first twelve chapters to refresh my knowledge and I learned lots of new things.
Can't wait to read the other chapters.
I particularly liked the intermediate problems, which allow you to build better intuition along the way.
Figurines are also really nice.

[Pascal Leroy @PaLeroy]

@prateekbhustali I would love to see a N vs N version!

[torchrl @torchrl1]

🎉 Exciting news! TorchRL paper has been accepted as a spotlight talk at @iclr_conf in Vienna this May! Huge thanks to the amazing OSS community, there would be no torchrl if it wasn't for our contributors. See you there! #ICLR2024 #Vienna

https://t.co/oL0tmcsDGU

[Pascal Leroy @PaLeroy]

@PabloGMorato Where are the selfies people?

[Pascal Leroy @PaLeroy]

IMP-MARL in #NeurIPS2023, it’s now!

[Pascal Leroy @PaLeroy]

We released IMP-MARL: a Suite of Environments for Large-scale
Infrastructure Management Planning via MARL.
In IMP-MARL, agents decide the inspections and repairs needed to limit the risk of system failure, based on the probability distributions of damage.
https://t.co/Qqrztqh3r4