Search Results for author: Mohammad Havaei

Found 25 papers, 7 papers with code

Pitfalls of Conditional Batch Normalization for Contextual Multi-Modal Learning

no code implementations28 Nov 2022 Ivaxi Sheth, Aamer Abdul Rahman, Mohammad Havaei, Samira Ebrahimi Kahou

Despite the boost in performance observed by using CBN layers, our work reveals that the visual features learned by introducing auxiliary data via CBN deteriorates.

Cancer type classification

FL Games: A Federated Learning Framework for Distribution Shifts

no code implementations31 Oct 2022 Sharut Gupta, Kartik Ahuja, Mohammad Havaei, Niladri Chatterjee, Yoshua Bengio

Federated learning aims to train predictive models for data that is distributed across clients, under the orchestration of a server.

Federated Learning

FHIST: A Benchmark for Few-shot Classification of Histological Images

no code implementations31 May 2022 Fereshteh Shakeri, Malik Boudiaf, Sina Mohammadi, Ivaxi Sheth, Mohammad Havaei, Ismail Ben Ayed, Samira Ebrahimi Kahou

We build few-shot tasks and base-training data with various tissue types, different levels of domain shifts stemming from various cancer sites, and different class-granularity levels, thereby reflecting realistic scenarios.

Classification Few-Shot Learning +1

FL Games: A federated learning framework for distribution shifts

no code implementations23 May 2022 Sharut Gupta, Kartik Ahuja, Mohammad Havaei, Niladri Chatterjee, Yoshua Bengio

Federated learning aims to train predictive models for data that is distributed across clients, under the orchestration of a server.

Federated Learning

CT-SGAN: Computed Tomography Synthesis GAN

no code implementations14 Oct 2021 Ahmad Pesaranghader, Yiping Wang, Mohammad Havaei

Diversity in data is critical for the successful training of deep learning models.

Lung Nodule Detection

Hypothesis Disparity Regularized Mutual Information Maximization

no code implementations15 Dec 2020 Qicheng Lao, Xiang Jiang, Mohammad Havaei

We propose a hypothesis disparity regularized mutual information maximization~(HDMI) approach to tackle unsupervised hypothesis transfer -- as an effort towards unifying hypothesis transfer learning (HTL) and unsupervised domain adaptation (UDA) -- where the knowledge from a source domain is transferred solely through hypotheses and adapted to the target domain in an unsupervised manner.

Transfer Learning Unsupervised Domain Adaptation

Conditional Generation of Medical Images via Disentangled Adversarial Inference

no code implementations8 Dec 2020 Mohammad Havaei, Ximeng Mao, Yiping Wang, Qicheng Lao

Current practices in using cGANs for medical image generation, only use a single variable for image generation (i. e., content) and therefore, do not provide much flexibility nor control over the generated image.

Data Augmentation Disentanglement +2

Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation

1 code implementation ICML 2020 Xiang Jiang, Qicheng Lao, Stan Matwin, Mohammad Havaei

We present an approach for unsupervised domain adaptation---with a strong focus on practical considerations of within-domain class imbalance and between-domain class distribution shift---from a class-conditioned domain alignment perspective.

Pseudo Label Unsupervised Domain Adaptation

Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders

no code implementations12 May 2020 Saeid Asgari Taghanaki, Mohammad Havaei, Alex Lamb, Aditya Sanghi, Ara Danielyan, Tonya Custis

The latent variables learned by VAEs have seen considerable interest as an unsupervised way of extracting features, which can then be used for downstream tasks.

DFNet: Discriminative feature extraction and integration network for salient object detection

1 code implementation3 Apr 2020 Mehrdad Noori, Sina Mohammadi, Sina Ghofrani Majelan, Ali Bahri, Mohammad Havaei

To address the second challenge, we propose an Attention-based Multi-level Integrator Module to give the model the ability to assign different weights to multi-level feature maps.

object-detection RGB Salient Object Detection +2

FoCL: Feature-Oriented Continual Learning for Generative Models

1 code implementation9 Mar 2020 Qicheng Lao, Mehrzad Mortazavi, Marzieh Tahaei, Francis Dutil, Thomas Fevens, Mohammad Havaei

In this paper, we propose a general framework in continual learning for generative models: Feature-oriented Continual Learning (FoCL).

Continual Learning Incremental Learning

CAGNet: Content-Aware Guidance for Salient Object Detection

3 code implementations29 Nov 2019 Sina Mohammadi, Mehrdad Noori, Ali Bahri, Sina Ghofrani Majelan, Mohammad Havaei

Beneficial from Fully Convolutional Neural Networks (FCNs), saliency detection methods have achieved promising results.

object-detection RGB Salient Object Detection +2

Learning to Learn with Conditional Class Dependencies

no code implementations ICLR 2019 Xiang Jiang, Mohammad Havaei, Farshid Varno, Gabriel Chartrand, Nicolas Chapados, Stan Matwin

Neural networks can learn to extract statistical properties from data, but they seldom make use of structured information from the label space to help representation learning.

Few-Shot Learning Representation Learning

InfoMask: Masked Variational Latent Representation to Localize Chest Disease

no code implementations28 Mar 2019 Saeid Asgari Taghanaki, Mohammad Havaei, Tess Berthier, Francis Dutil, Lisa Di Jorio, Ghassan Hamarneh, Yoshua Bengio

The scarcity of richly annotated medical images is limiting supervised deep learning based solutions to medical image analysis tasks, such as localizing discriminatory radiomic disease signatures.

Multiple Instance Learning

Learnable Explicit Density for Continuous Latent Space and Variational Inference

no code implementations6 Oct 2017 Chin-wei Huang, Ahmed Touati, Laurent Dinh, Michal Drozdzal, Mohammad Havaei, Laurent Charlin, Aaron Courville

In this paper, we study two aspects of the variational autoencoder (VAE): the prior distribution over the latent variables and its corresponding posterior.

Density Estimation Variational Inference

HeMIS: Hetero-Modal Image Segmentation

1 code implementation18 Jul 2016 Mohammad Havaei, Nicolas Guizard, Nicolas Chapados, Yoshua Bengio

We introduce a deep learning image segmentation framework that is extremely robust to missing imaging modalities.

Image Segmentation Imputation +1

Deep learning trends for focal brain pathology segmentation in MRI

no code implementations18 Jul 2016 Mohammad Havaei, Nicolas Guizard, Hugo Larochelle, Pierre-Marc Jodoin

In this chapter, we provide a survey of CNN methods applied to medical imaging with a focus on brain pathology segmentation.

BIG-bench Machine Learning Medical Diagnosis

Within-Brain Classification for Brain Tumor Segmentation

no code implementations5 Oct 2015 Mohammad Havaei, Hugo Larochelle, Philippe Poulin, Pierre-Marc Jodoin

Purpose: In this paper, we investigate a framework for interactive brain tumor segmentation which, at its core, treats the problem of interactive brain tumor segmentation as a machine learning problem.

BIG-bench Machine Learning Brain Tumor Segmentation +3

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