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51a472c08e21aef54ed749806e3e6490-Paper.pdf

Neural Information Processing Systems

Another possible reason is that it is unclear if the low signal-to-noise ratio of neuroimaging tools such as functional Magnetic Resonance Imaging (fMRI) can allow us to reveal the correlates of complex (and perhaps subtle) syntactic representations.




Temporally-ConsistentSurvivalAnalysis

Neural Information Processing Systems

Wemodel theeventofinterest asaspecial terminal state, andwe seek to estimate the survival distribution (i.e., the distribution of the hitting time for that terminal state) from anyother state.



FactorGraphNeuralNetwork

Neural Information Processing Systems

Most of the successful deep neural network architectures are structured, often consisting of elements like convolutional neural networks and gated recurrent neural networks. Recently, graph neural networks (GNNs) have been successfully applied to graph-structureddata such as point cloud and molecular data. These networks often only consider pairwise dependencies, as they operate on a graph structure.




60495b4e033e9f60b32a6607b587aadd-Paper.pdf

Neural Information Processing Systems

Furthermore, weprove information theoretic lower bounds which establish minimax optimality of the skillparameter estimation technique usedinouralgorithm. These bounds utilize a continuum version of Fano's method along with a careful covering argument.