Mina Rezaei | DeepAI

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∙ 09/05/2023

Probabilistic Self-supervised Learning via Scoring Rules Minimization

In this paper, we propose a novel probabilistic self-supervised learning...

0 Amirhossein Vahidi, et al. ∙

∙ 08/28/2023

Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning

Ensembling a neural network is a widely recognized approach to enhance m...

0 Amirhossein Vahidi, et al. ∙

∙ 05/25/2023

Efficient Document Embeddings via Self-Contrastive Bregman Divergence Learning

Learning quality document embeddings is a fundamental problem in natural...

0 Daniel Saggau, et al. ∙

∙ 03/14/2023

Young Humans Make Change, Young Users Click: Creating Youth-Centered Networked Social Movements

From the urbanists' perspective, the everyday experience of young people...

0 Mina Rezaei, et al. ∙

∙ 09/14/2022

Joint Debiased Representation and Image Clustering Learning with Self-Supervision

Contrastive learning is among the most successful methods for visual rep...

8 Shunjie-Fabian Zheng, et al. ∙

∙ 09/13/2022

Evaluating User Experience in Literary and Film Geography-based Apps with a Cartographical User-Centered Design Lens

Geography scholarship currently includes interdisciplinary approaches an...

0 Mina Rezaei, et al. ∙

∙ 09/06/2022

Robust and Efficient Imbalanced Positive-Unlabeled Learning with Self-supervision

Learning from positive and unlabeled (PU) data is a setting where the le...

7 Emilio Dorigatti, et al. ∙

∙ 01/31/2022

Positive-Unlabeled Learning with Uncertainty-aware Pseudo-label Selection

Pseudo-labeling solutions for positive-unlabeled (PU) learning have the ...

12 Emilio Dorigatti, et al. ∙

∙ 09/22/2021

Deep Variational Clustering Framework for Self-labeling of Large-scale Medical Images

We propose a Deep Variational Clustering (DVC) framework for unsupervise...

0 Farzin Soleymani, et al. ∙

∙ 09/15/2021

Deep Bregman Divergence for Contrastive Learning of Visual Representations

Deep Bregman divergence measures divergence of data points using neural ...

0 Mina Rezaei, et al. ∙

∙ 09/11/2021

Learning Statistical Representation with Joint Deep Embedded Clustering

One of the most promising approaches for unsupervised learning is combin...

17 Mina Rezaei, et al. ∙

∙ 11/22/2018

Multi-Task Generative Adversarial Network for Handling Imbalanced Clinical Data

We propose a new generative adversarial architecture to mitigate imbalan...

0 Mina Rezaei, et al. ∙

∙ 11/05/2018

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different d...

0 Spyridon Bakas, et al. ∙

∙ 10/09/2018

Conditional Generative Refinement Adversarial Networks for Unbalanced Medical Image Semantic Segmentation

We propose a new generative adversarial architecture to mitigate imbalan...

6 Mina Rezaei, et al. ∙

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