15 citations · 61 across the 31 of their papers we have counts for
37 papers
Grounding Social Perception in Intuitive Physics
Lance Ying, Aydan Y. Huang, Aviv Netanyahu +4
People infer rich social information from others' actions. These inferences are often constrained by the physical world: what agents can do, what obstacles permit, and how the phys…
Network of Theseus (like the ship)
Vighnesh Subramaniam, Colin Conwell, Boris Katz +2
A standard assumption in deep learning is that the inductive bias introduced by a neural network architecture must persist from training through inference. The architecture you tra…
Neuroprobe: Evaluating Intracranial Brain Responses to Naturalistic Stimuli
Andrii Zahorodnii, Christopher Wang, Geeling Chau +7
High-resolution neural datasets enable foundation models for the next generation of brain-computer interfaces and neurological treatments. The community requires rigorous benchmark…
Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli
Christopher Wang, Adam Uri Yaari, Aaditya K Singh +10
We present the Brain Treebank, a large-scale dataset of electrophysiological neural responses, recorded from intracranial probes while 10 subjects watched one or more Hollywood mov…
BrainBits: How Much of the Brain are Generative Reconstruction Methods Using?
David Mayo, Christopher Wang, Asa Harbin +4
When evaluating stimuli reconstruction results it is tempting to assume that higher fidelity text and image generation is due to an improved understanding of the brain or more powe…
Using Multimodal Deep Neural Networks to Disentangle Language from Visual Aesthetics
Colin Conwell, Christopher Hamblin, Chelsea Boccagno +4
When we experience a visual stimulus as beautiful, how much of that experience derives from perceptual computations we cannot describe versus conceptual knowledge we can readily tr…