Aswin Paul
@aswinpaule
Trying to figure out how we understand and act in the world. | PhD student 👨🏫| Physics 💫| Neuroscience 🧠 | Intelligence 🤖
ID: 1429088462972411910
https://github.com/aswinpaul 21-08-2021 14:30:27
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Great work by Aswin Paul reducing the computational complexity of sophisticated #active #inference by orders of magnitude:
The amazing team who made this possible: Moein Khajehnejad Aswin Paul Adeel Razi Brett J. Kagan Cortical Labs arxiv.org/abs/2405.16946 #AI #NeuroAI #ReinforcementLearning #MachineLearning #Neuroscience #SampleEfficiency
Amazing work from Cortical Labs and Monash Biomedical Imaging. Many more to come!
8/8 Special thanks to my co-authors Forough Habibollahi , Aswin Paul , Adeel Razi , and Brett J. Kagan . Your collaboration made this possible! 👏 Turner Institute for Brain and Mental Health Cortical Labs
Aswin is putting paper after paper from his PhD thesis. Have a look at the thread. Awesome collaboration with Takuya Isomura at RIKEN Center for Brain Science
It was such a great symposium on naturalistic imaging with Emily Finn, The LAB Lab 🏳️🌈🏳️⚧️, Hongmi Lee, Asirh Zadbood, together with Sadia Shakil at #OHBM2024
Excited to share the first paper of my PhD: Towards a theory of learning dynamics in deep state space models arxiv.org/abs/2407.07279 with Jimmy Smith, Michael Kleinman, Dan Biderman, and Scott Linderman. Accepted as a Spotlight talk at the NGSM workshop at ICML 2024!
📢We're delighted to organise NeuroAI workshop at this year's NeurIPS Conference 2024 (excuse the typo in the graphic). Accepting submissions (4 pages + supp): neuroai-workshop.github.io Highlight: In-person panel with Yoshua Bengio and Karl Friston Follow NeuroAI Workshop @ NeurIPS2024 for details
📢 Attention! Pleased to announce we are organizing the 1st NeuroAI workshop NeurIPS Conference 2024! Deadline for submissions: 7th September More details: neuroai-workshop.github.io Follow NeuroAI Workshop @ NeurIPS2024 Forough Habibollahi Adeel Razi Noor Sajid Jason Eshraghian Tony Zador Yoshua Bengio
Article | From pixels to planning: scale-free active inference Coauthors: Conor Heins, Tim Verbelen, Lancelot Da Costa, Tommaso Salvatori, Dimitrije Markovic, Alexander Tschantz, Magnus Koudahl, Chris L Buckley, Thomas Parr arxiv.org/pdf/2407.20292
Exciting news! Nature Machine Intelligence has featured our work on decentralized multi-agent reinforcement learning for large-scale networked control, on cracking the scaling challenge of #MARL. The article is open access: nature.com/articles/s4225… Nature Portfolio Nature Machine Intelligence