5 accepted papers
The deep operator networks (DON), a class of neural operators that learn mappings between function spaces, have recently emerged as surrogate models for parametric partial differential equations (PDEs). However, their full potential for accurately approximating general black-box PDEs remains underex
Decoding semantic meanings from brain activity has attracted increasing attention. Neurolinguists have found that semantic perception is open to multisensory stimulation, as word meanings can be delivered by both auditory and visual inputs. Prior work which decodes semantic meanings from neuroimagin…
Brain activation can reflect semantic information elicited by natural words and concepts. Increasing research has been conducted on decoding such neural activation patterns using representational semantic models. However, prior work decoding semantic meaning from neurophysiological responses has bee…
Real human language mechanisms and the artificial intelligent language processing methods are two independent systems. Exploring the relationship between the two can help develop human-like language models and is also beneficial to reveal the neuroscience of the reading brain. The flourishing resear…
Machine reading is a fundamental task for testing the capability of natural language understand- ing, which is closely related to human cognition in many aspects. With the rising of deep learning techniques, algorithmic models rival human performances on simple QA, and thus increasingly challenging…