@steleac
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PhD Student @EdinburghUni; studying temporally extended behaviours in both single and multi-agent RL
Joined August 2019
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Really excited to present our recent work at #ICLR2026 this week!
We discover highly coordinated joint behaviours and integrate them into the skill sets of MARL agents, accelerating the search for effective joint strategies in downstream tasks.🧵
Paper: raulsteleac.github.io/iaro
Raul Steleac retweeted
A good reason for my first post! A few weeks ago, our paper Assistax received an Outstanding Paper Award at #RLC2026 🎉
Assistax is a GPU-accelerated RL benchmark for assistive robotics.
Huge thanks to @RL_Conference for the recognition!
More below 👇
Raul Steleac retweeted
We’re open-sourcing the models, weights and training code for PERSIST, our 1.7B parameter 3D world model!
By modelling a dynamic 3D world state instead of relying on pixel histories, PERSIST generates experiences that remain spatially and temporally coherent over thousands of steps.
Tom, @kaixin20578389 and I will present PERSIST at @icmlconf in Seoul next month. See you there!
Links in thread⬇️
#WorldModels #ICML2026
Raul Steleac retweeted
Nice! (could not resist) – at Atlanta, GA
🚨 Are neural implicit representations applicable for larger-scale SLAM? Check out our NICE-SLAM👍! #CVPR2022
NICE website: pengsongyou.github.io/nice-s…
NICE code: github.com/cvg/nice-slam
NICE collaborations w/ Zihan Zhu (undergrad) @visionviktor @Martin_R_Oswald @mapo1 et al.
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Raul Steleac retweeted
A lot of people complain that RL doesn't work and RL researchers are still playing games. While this criticism is true to some extent, there's been a new trend of applying RL for real-life problems. This is a thread of notable papers split by the topic.
1/n
Raul Steleac retweeted
23 and 24 year olds able to book their NHS vaccine appointments from tomorrow.
Raul Steleac retweeted
Discover how WaveNet has evolved from research concept to advanced real-world system that creates more natural-sounding speech and helps @Google unblock communication barriers for millions of people around the world: dpmd.ai/wavenet
Raul Steleac retweeted
Diffusion Models Beat GANs on Image Synthesis
Achieves 3.85 FID on ImageNet 512×512 and matches BigGAN-deep even with as few as 25 forward passes per sample, all while maintaining better coverage of the distribution.
arxiv.org/abs/2105.05233
Raul Steleac retweeted
Today @iclr_conf
- Women in Machine Learning (@WIML) at 2PM
- Philosophy and AGI at 5PM with @dabelcs, @clarelyle and @jakeABeck (@UniOfOxford)
There are also various poster sessions happening today from 5PM - see the full schedule here: dpmd.ai/ICLR21 #ICLR2021
Raul Steleac retweeted
In addition to MT-Opt, we are releasing Actionable Models, which addresses the problem of defining tasks (which becomes quite cumbersome at scale). This work uses the dataset collected by MT-Opt but uses goal-conditioned offline Q-learning to learn a general goal-reaching policy.
Excited to present our new work on Actionable Models, an approach for learning functional understanding of the world via goal-conditioned Q-functions in a fully-offline setting!
paper: arxiv.org/abs/2104.07749
website: actionable-models.github.io
youtube.com/watch?v=S3SCR7iY…
Raul Steleac retweeted
Most RL agents assume that rewards are caused by recent actions, and learn slowly when this isn't true.
This new method speeds up learning in tasks with delayed reward by learning to link related events - regardless of how much time separates them.
dpmd.ai/12425
Raul Steleac retweeted
Thrilled to announce our first major breakthrough in applying AI to a grand challenge in science. #AlphaFold has been validated as a solution to the ‘protein folding problem’ & we hope it will have a big impact on disease understanding and drug discovery: deepmind.com/alphafold-blog
Raul Steleac retweeted
Everyone has heard about fast.ai or CS231n (for a good reason), but did you know you can access Stanford’s CS224w ML with Graphs or download the book Elements of Causal Inference for free? Thread on underappreciated ML resources 📚🎥 that deserve more love 👇 /1
