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Workflow Provenance in the Lifecycle of Scientific Machine Learning
Machine Learning (ML) has already fundamentally changed several business...
09/30/2020 ∙ by Renan Souza, et al. ∙
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Effective Integration of Symbolic and Connectionist Approaches through a Hybrid Representation
In this paper, we present our position for a neuralsymbolic integration ...
12/18/2019 ∙ by Marcio Moreno, et al. ∙
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Managing Machine Learning Workflow Components
Machine Learning Workflows (MLWfs) have become essential and a disruptiv...
12/10/2019 ∙ by Marcio Moreno, et al. ∙
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Provenance Data in the Machine Learning Lifecycle in Computational Science and Engineering
Machine Learning (ML) has become essential in several industries. In Com...
10/09/2019 ∙ by Renan Souza, et al. ∙
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Semantic Segmentation of Seismic Images
Almost all work to understand Earth's subsurface on a large scale relies...
05/10/2019 ∙ by Daniel Civitarese, et al. ∙
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Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation
Machine learning and, more specifically, deep learning algorithms have s...
03/26/2019 ∙ by Reinaldo Mozart Silva, et al. ∙
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Penobscot Dataset: Fostering Machine Learning Development for Seismic Interpretation
We have seen in the past years the flourishing of machine and deep learn...
03/21/2019 ∙ by Lais Baroni, et al. ∙
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