recognition model
CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities [ Supplementary Material ]
To facilitate these annotations, we used both our user application and Label Studio.
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DesCo: Learning Object Recognition with Rich Language Descriptions
Recent development in vision-language approaches has instigated a paradigm shift in learning visual recognition models from language supervision. These approaches align objects with language queries (e.g. "a photo of a cat") and thus improve the models' adaptability to novel objects and domains.
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A neurally plausible model learns successor representations in partially observable environments
Neural Information Processing Systems http://nips.cc/
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- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
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- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Undirected Networks > Markov Models (0.48)
Graphical Generative Adversarial Networks
Chongxuan LI, Max Welling, Jun Zhu, Bo Zhang
Neural Information Processing Systems http://nips.cc/
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Tensor Monte Carlo: Particle Methods for the GPU era
Neural Information Processing Systems http://nips.cc/
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- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty (0.94)
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Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction
Kevin Ellis, Lucas Morales, Mathias Sablé-Meyer, Armando Solar-Lezama, Josh Tenenbaum
Neural Information Processing Systems http://nips.cc/
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2 ProblemFormulationandRelatedWorks Intypical graph learning problems, givenasetoflabeled graphsDtr ={(Gi,yi)}N
In this paper, we first mathematically formulate thetwochallenging problems forgraph data andtake an initiative on tackling them under a unified probabilistic model.
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