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03/06/2022
Divide and Conquer: Text Semantic Matching with Disentangled Keywords and Intents
Text semantic matching is a fundamental task that has been widely used i...
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05/04/2021
Deep-learning-based coupled flow-geomechanics surrogate model for CO_2 sequestration
A deep-learning-based surrogate model capable of predicting flow and geo...
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05/11/2020
FroDO: From Detections to 3D Objects
Object-oriented maps are important for scene understanding since they jo...
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10/21/2019
Multiphase flow prediction with deep neural networks
This paper proposes a deep neural network approach for predicting multip...
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08/16/2019
A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems
A deep-learning-based surrogate model is developed and applied for predi...
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06/19/2019
Learning Compressed Sentence Representations for On-Device Text Processing
Vector representations of sentences, trained on massive text corpora, ar...
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09/07/2018
ADM for grid CRF loss in CNN segmentation
Variants of gradient descent (GD) dominate CNN loss minimization in comp...
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05/12/2018
Constrained-CNN losses forweakly supervised segmentation
Weak supervision, e.g., in the form of partial labels or image tags, is ...
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04/04/2018
Normalized Cut Loss for Weakly-supervised CNN Segmentation
Most recent semantic segmentation methods train deep convolutional neura...
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03/26/2018
On Regularized Losses for Weakly-supervised CNN Segmentation
Minimization of regularized losses is a principled approach to weak supe...
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05/16/2017
Kernel clustering: density biases and solutions
Kernel methods are popular in clustering due to their generality and dis...
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06/24/2015
