Anirudh GJ
@anirudhgj.bsky.social
NeuroAI PhD student @ Mila & Universite de Montreal w/ Prof. Matthew Perich.
Studying continual learning and adaptation in Brain and ANNs.
Studying continual learning and adaptation in Brain and ANNs.
Reposted by Anirudh GJ
Mice learn these tasks and are robust to perturbations like fog. Now, we invite you all to make AI agents to beat mice.
We present our #NeurIPS competition. You can learn about it here: robustforaging.github.io (7/n)
We present our #NeurIPS competition. You can learn about it here: robustforaging.github.io (7/n)
July 10, 2025 at 12:22 PM
Mice learn these tasks and are robust to perturbations like fog. Now, we invite you all to make AI agents to beat mice.
We present our #NeurIPS competition. You can learn about it here: robustforaging.github.io (7/n)
We present our #NeurIPS competition. You can learn about it here: robustforaging.github.io (7/n)
Reposted by Anirudh GJ
"These findings validate core predictions of Spatial Computing by showing that oscillatory dynamics not only gate information in time but also shape where in the cortex cognitive content is represented."
More on Spatial Computing:
doi.org/10.1038/s414...
More on Spatial Computing:
doi.org/10.1038/s414...
Working memory control dynamics follow principles of spatial computing - Nature Communications
It is unclear how cognitive computations are performed on sensory information. Here, neural evidence from working memory tasks suggests that the physical dimensions of cortical networks are used to up...
doi.org
June 25, 2025 at 5:40 PM
"These findings validate core predictions of Spatial Computing by showing that oscillatory dynamics not only gate information in time but also shape where in the cortex cognitive content is represented."
More on Spatial Computing:
doi.org/10.1038/s414...
More on Spatial Computing:
doi.org/10.1038/s414...
Reposted by Anirudh GJ
I think the biological evidence points to this not being the case. We can see instances where synapses literally undergo a form of reverse plasticity, e.g. see here: www.cell.com/trends/cogni...
I think it cannot be assumed that we never wipe memories from our brains completely!
I think it cannot be assumed that we never wipe memories from our brains completely!
www.cell.com
January 24, 2025 at 11:10 PM
I think the biological evidence points to this not being the case. We can see instances where synapses literally undergo a form of reverse plasticity, e.g. see here: www.cell.com/trends/cogni...
I think it cannot be assumed that we never wipe memories from our brains completely!
I think it cannot be assumed that we never wipe memories from our brains completely!
I love how this paper uses cortico-thalamic interactions(context switching) for continual learning.
arxiv.org/abs/2205.11713
arxiv.org/abs/2205.11713
Thalamus: a brain-inspired algorithm for biologically-plausible continual learning and disentangled representations
Animals thrive in a constantly changing environment and leverage the temporal structure to learn well-factorized causal representations. In contrast, traditional neural networks suffer from forgetting...
arxiv.org
January 6, 2025 at 1:00 PM
I love how this paper uses cortico-thalamic interactions(context switching) for continual learning.
arxiv.org/abs/2205.11713
arxiv.org/abs/2205.11713
Reposted by Anirudh GJ
There is also this one: www.sciencedirect.com/science/arti...
Single cortical neurons as deep artificial neural networks
Utilizing recent advances in machine learning, we introduce a systematic approach to characterize neurons’ input/output (I/O) mapping complexity. Deep…
www.sciencedirect.com
December 16, 2024 at 8:34 PM
There is also this one: www.sciencedirect.com/science/arti...