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Learning to Predict Citation-Based Impact Measures
TLDR
This paper investigates the problem of predicting scienti c impact for individual authors and papers up to 10 years into the future. Expand
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RoboTHOR: An Open Simulation-to-Real Embodied AI Platform
TLDR
We introduce RoboTHOR to democratize research in interactive and embodied visual AI. Expand
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Determinantal Generalizations of Instrumental Variables
Abstract Linear structural equation models relate the components of a random vector using linear interdependencies and Gaussian noise. Each such model can be naturally associated with a mixed graphExpand
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Grounded Situation Recognition
TLDR
We introduce Grounded Situation Recognition, a task that requires producing structured semantic summaries of images describing: the primary activity, entities engaged in the activity with their roles (e.g. agent, tool), and bounding-box groundings of entities. Expand
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AllenAct: A Framework for Embodied AI Research
TLDR
We introduce AllenAct, a modular and flexible learning framework designed with a focus on the unique requirements of Embodied AI research. Expand
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Generic Identifiability of Linear Structural Equation Models by Ancestor Decomposition
Linear structural equation models, which relate random variables via linear interdependencies and Gaussian noise, are a popular tool for modelling multivariate joint distributions. The modelsExpand
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Efficient computation of the Bergsma–Dassios sign covariance
TLDR
In an extension of Kendall’s $$\tau $$τ, Bergsma and Dassios introduced a covariance measure for two ordinal random variables that vanishes if and only if the two variables are independent. Expand
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Gender trends in computer science authorship
TLDR
This paper presents a comprehensive and up-to-date analysis of gender trends in the Computer Science literature (ranging from 1970 through 2018). Expand
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Two Body Problem: Collaborative Visual Task Completion
TLDR
We study the problem of learning to collaborate directly from pixels in AI2-THOR and demonstrate the benefits of explicit and implicit modes of communication to perform visual tasks. Expand
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Marginal likelihood and model selection for Gaussian latent tree and forest models
Gaussian latent tree models, or more generally, Gaussian latent forest models have Fisher-information matrices that become singular along interesting submodels, namely, models that correspond toExpand
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