M. Baghshah

发表

Mahdieh Soleymani Baghshah, Marzieh Gheisari, Adeleh Bitarafan, 2016, IEEE Transactions on Knowledge and Data Engineering.

CCGG: A Deep Autoregressive Model for Class-Conditional Graph Generation

H. Rabiee, M. Baghshah, Amirmojtaba Sabour, 2021, WWW.

A Novel Semi-supervised Clustering Algorithm for Finding Clusters of Arbitrary Shapes

M. Baghshah, S. B. Shouraki, 2008, CSICC.

Deep Graph Generators: A Survey pdf

Hamid R. Rabiee, Mahdieh Soleymani Baghshah, Faezeh Faez, 2020, IEEE Access.

RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data

Hamid R. Rabiee, Nassir Navab, Mahdieh Soleymani Baghshah, 2021, Medical image analysis.

HEROHE Challenge: Predicting HER2 Status in Breast Cancer from Hematoxylin–Eosin Whole-Slide Imaging

Kele Xu, C. Eloy, M. Baghshah, 2022, J. Imaging.

SCGG: A deep structure-conditioned graph generative model

H. Rabiee, M. Baghshah, Faezeh Faez, 2022, PloS one.

Isoform Function Prediction Using Deep Neural Network

M. Baghshah, S. Motahari, Ali Rasteh, 2022, ArXiv.

BIMRL: Brain Inspired Meta Reinforcement Learning

M. Baghshah, Seyed Roozbeh Razavi Rohani, Saeed Hedayatian, 2022, ArXiv.

Transformer-based deep neural network language models for Alzheimer’s disease detection from targeted speech

H. Aghajan, M. Baghshah, A. Roshanzamir, 2020 .

A Distinct Unsupervised Reference Model From The Environment Helps Continual Learning

M. Baghshah, Seyyed AmirHossein Ameli Kalkhoran, Mohammadamin Banayeeanzade, 2023, ArXiv.

Finding Arbitrary Shaped Clusters and Color Image Segmentation

S.B. Shouraki, M.S. Baghshah, M. Baghshah, 2008, 2008 Congress on Image and Signal Processing.

MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge

Lisheng Wang, Dwarikanath Mahapatra, Mahdieh Soleymani Baghshah, 2021, IEEE Transactions on Medical Imaging.

HEROHE Challenge: Predicting HER2 Status in Breast Cancer from Hematoxylin–Eosin Whole-Slide Imaging pdf

Catarina Eloy, Mahdieh Soleymani Baghshah, Vincenzo Della Mea, 2021, J. Imaging.

Non-linear metric learning using pairwise similarity and dissimilarity constraints and the geometrical structure of data

Mahdieh Soleymani Baghshah, Saeed Bagheri Shouraki, M. Baghshah, 2010, Pattern Recognit..

Unsupervised domain adaptation via representation learning and adaptive classifier learning

Mahdieh Soleymani Baghshah, Marzieh Gheisari, M. Baghshah, 2015, Neurocomputing.

RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data

N. Navab, H. Rabiee, M. Baghshah, 2021, Medical Image Anal..

Kernel-based metric learning for semi-supervised clustering

Mahdieh Soleymani Baghshah, Saeed Bagheri Shouraki, M. Baghshah, 2010, Neurocomputing.

Isoform Function Prediction Using Deep Neural Network

M. Baghshah, S. Motahari, Ali Rasteh, 2022, ArXiv.

Evolving fuzzy classifiers using a symbiotic approach

Caro Lucas, Mahdieh Soleymani Baghshah, Saeed Bagheri Shouraki, 2007, 2007 IEEE Congress on Evolutionary Computation.

Jointly Measuring Diversity and Quality in Text Generation Models pdf

Mahdieh Soleymani Baghshah, Ehsan Montahaei, Danial Alihosseini, 2019, Proceedings of the Workshop on Methods for Optimizing and Evaluating Neural Language Generation.

Paraphrase Generation by Learning How to Edit from Samples

Mahdieh Soleymani Baghshah, Mohammadreza Salehi, Amirhossein Kazemnejad, 2020, ACL.

A fuzzy clustering algorithm for finding arbitrary shaped clusters

Mahdieh Soleymani Baghshah, Saeed Bagheri Shouraki, M. Baghshah, 2008, 2008 IEEE/ACS International Conference on Computer Systems and Applications.

An agent-based clustering algorithm using potential fields

Caro Lucas, Mahdieh Soleymani Baghshah, Saeed Bagheri Shouraki, 2008, 2008 IEEE/ACS International Conference on Computer Systems and Applications.

Classification of 12-lead ECG Signals With Adversarial Multi-Source Domain Generalization

M. Baghshah, Hosein Hasani, Adeleh Bitarafan, 2020, 2020 Computing in Cardiology.

Universal Adversarial Attacks on Text Classifiers

Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard, Mahdieh Soleymani Baghshah, 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Adversarial Classifier for Imbalanced Problems pdf

Hamid R. Rabiee, Mahdieh Soleymani Baghshah, Mahsa Ghorbani, 2018, ArXiv.

MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional Networks

Hamid R. Rabiee, Mahdieh Soleymani Baghshah, Mahsa Ghorbani, 2018, 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

A Hybrid Deep Model for Automatic Arrhythmia Classification based on LSTM Recurrent Networks

Mahdieh Soleymani Baghshah, Hamidreza Khodajou-Chokami, Adeleh Bitarafan, 2020, 2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA).

DGSAN: Discrete Generative Self-Adversarial Network

Mahdieh Soleymani Baghshah, Ehsan Montahaei, Danial Alihosseini, 2019, Neurocomputing.

Joint predictive model and representation learning for visual domain adaptation

Mahdieh Soleymani Baghshah, Marzieh Gheisari, M. Baghshah, 2017, Eng. Appl. Artif. Intell..

An Efficient Semi-Supervised Multi-label Classifier Capable of Handling Missing Labels

Mahdieh Soleymani Baghshah, Amirhossein Hosseini Akbarnejad, M. Baghshah, 2019, IEEE Transactions on Knowledge and Data Engineering.

An Efficient Large-scale Semi-supervised Multi-label Classifier Capable of Handling Missing labels pdf

Mahdieh Soleymani Baghshah, Amirhossein Akbarnejad, M. Baghshah, 2016, ArXiv.

Multi-modal deep distance metric learning

Mahdieh Soleymani Baghshah, Ehsan Imani, Seyed Mahdi Roostaiyan, 2017, Intell. Data Anal..

Supplementary Materials for "Generative vs Discriminative: Rethinking The Meta-Continual Learning"

M. Baghshah, Mohammadamin Banayeeanzade, Hosein Hasani, 2021 .

Semi-supervised Zero-Shot Learning by a Clustering-based Approach pdf

Mahdieh Soleymani Baghshah, Seyed Mohsen Shojaee, M. Baghshah, 2016, ArXiv.

Personalized Computational Human Phantoms via a Hybrid Model-based Deep Learning Method

Mahdieh Soleymani Baghshah, Hamidreza Khodajou-Chokami, Adeleh Bitarafan, 2020, 2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA).

Semi-Supervised Metric Learning Using Pairwise Constraints

M. Baghshah, S. Shouraki, 2009, IJCAI.

MDL-CW: A Multimodal Deep Learning Framework with CrossWeights

Hamid R. Rabiee, Mahdieh Soleymani Baghshah, Sarah Rastegar, 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference

Hamid R. Rabiee, Nassir Navab, Mahdieh Soleymani Baghshah, 2021, MICCAI.

DGSAN: Discrete Generative Self-Adversarial Network

M. Baghshah, Ehsan Montahaei, Danial Alihosseini, 2019, Neurocomputing.

A Novel Fuzzy Classifier using Fuzzy LVQ to Recognize Online Persian Handwriting

S.B. Shouraki, S. Kasaei, M.S. Baghshah, 2006, 2006 2nd International Conference on Information & Communication Technologies.

Classification of Breast Cancer Histopathology Images using a Modified Supervised Contrastive Learning Method

M. Baghshah, Ali Royat, Matina Mahdizadeh Sani, 2024, ArXiv.