167 citations · 643 across the 22 of their papers we have counts for
22 papers
Contravariance Theory: Strong Alignment for Minimal Solutions to Hard Tasks
Dan Yamins, Aran Nayebi
A series of results from the NeuroAI over the past fifteen years have raised core questions both about how to compare Deep Neural Network (DNN) models to the brain, and about how m…
Model-brain comparison using inter-animal transforms
Imran Thobani, Javier Sagastuy-Brena, Aran Nayebi +3
Artificial neural network models have emerged as promising mechanistic models of the brain. However, there is little consensus on the correct method for comparing model activations…
Task-Optimized Convolutional Recurrent Networks Align with Tactile Processing in the Rodent Brain
Trinity Chung, Yuchen Shen, Nathan C. L. Kong +1
Tactile sensing remains far less understood in neuroscience and less effective in artificial systems compared to more mature modalities such as vision and language. We bridge these…
On the Riemann Hypothesis and Hilbert's Tenth Problem
Aran Nayebi
The Riemann hypothesis is one of the most famous unresolved problems in modern mathematics. The discussion here will present an overview of past methods that prove the Riemann hypo…
Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes
Aran Nayebi, Rishi Rajalingham, Mehrdad Jazayeri +1
Humans and animals have a rich and flexible understanding of the physical world, which enables them to infer the underlying dynamical trajectories of objects and events, plausible…
Identifying Learning Rules From Neural Network Observables
Aran Nayebi, Sanjana Srivastava, Surya Ganguli +1
The brain modifies its synaptic strengths during learning in order to better adapt to its environment. However, the underlying plasticity rules that govern learning are unknown. Ma…