Daniel Civitarese | DeepAI

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∙ 02/05/2021

A modular framework for extreme weather generation

Extreme weather events have an enormous impact on society and are expect...

7 Bianca Zadrozny, et al. ∙

∙ 09/30/2020

Workflow Provenance in the Lifecycle of Scientific Machine Learning

Machine Learning (ML) has already fundamentally changed several business...

58 Renan Souza, et al. ∙

∙ 12/18/2019

Effective Integration of Symbolic and Connectionist Approaches through a Hybrid Representation

In this paper, we present our position for a neuralsymbolic integration ...

0 Marcio Moreno, et al. ∙

∙ 12/10/2019

Managing Machine Learning Workflow Components

Machine Learning Workflows (MLWfs) have become essential and a disruptiv...

0 Marcio Moreno, et al. ∙

∙ 10/09/2019

Provenance Data in the Machine Learning Lifecycle in Computational Science and Engineering

Machine Learning (ML) has become essential in several industries. In Com...

0 Renan Souza, et al. ∙

∙ 05/10/2019

Semantic Segmentation of Seismic Images

Almost all work to understand Earth's subsurface on a large scale relies...

0 Daniel Civitarese, et al. ∙

∙ 03/26/2019

Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation

Machine learning and, more specifically, deep learning algorithms have s...

0 Reinaldo Mozart Silva, et al. ∙

∙ 03/21/2019

Penobscot Dataset: Fostering Machine Learning Development for Seismic Interpretation

We have seen in the past years the flourishing of machine and deep learn...

0 Lais Baroni, et al. ∙

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