Joseph Paul Cohen

Orcid: 0000-0002-1334-3059

Affiliations:
  • Mila - Quebec AI Institute, Montreal, QC, Canada
  • University of Massachusetts Boston, Department of Computer Science, MA, USA


According to our database1, Joseph Paul Cohen authored at least 67 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Merlin: A Vision Language Foundation Model for 3D Computed Tomography.
CoRR, 2024

CheXagent: Towards a Foundation Model for Chest X-Ray Interpretation.
CoRR, 2024

2023
Identifying Spurious Correlations using Counterfactual Alignment.
CoRR, 2023

The Effect of Counterfactuals on Reading Chest X-rays.
CoRR, 2023

CheXstray: A Real-Time Multi-Modal Monitoring Workflow for Medical Imaging AI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

2022
The promise of machine learning applications in solid organ transplantation.
npj Digit. Medicine, 2022

Medical Image Segmentation Review: The success of U-Net.
CoRR, 2022

CheXstray: Real-time Multi-Modal Data Concordance for Drift Detection in Medical Imaging AI.
CoRR, 2022

TorchXRayVision: A library of chest X-ray datasets and models.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

2021
ivadomed: A Medical Imaging Deep Learning Toolbox.
J. Open Source Softw., 2021

Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction Models.
CoRR, 2021

Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Progressive Exaggeration on Chest X-rays.
CoRR, 2021

Deep semantic segmentation of natural and medical images: a review.
Artif. Intell. Rev., 2021

Exploring the Wasserstein metric for time-to-event analysis.
Proceedings of AAAI Symposium on Survival Prediction, 2021

Benefits of Linear Conditioning for Segmentation using Metadata.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

Simultaneous Similarity-based Self-Distillation for Deep Metric Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Saliency is a Possible Red Herring When Diagnosing Poor Generalization.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
ivadomed: A Medical Imaging Deep Learning Toolbox.
CoRR, 2020

S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning.
CoRR, 2020

A Benchmark of Medical Out of Distribution Detection.
CoRR, 2020

COVID-19 Image Data Collection: Prospective Predictions Are the Future.
CoRR, 2020

Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning.
CoRR, 2020

COVID-19 Image Data Collection.
CoRR, 2020

Spine intervertebral disc labeling using a fully convolutional redundant counting model.
CoRR, 2020

Automatic segmentation of spinal multiple sclerosis lesions: How to generalize across MRI contrasts?
CoRR, 2020

Factorized embeddings learns rich and biologically meaningful embedding spaces using factorized tensor decomposition.
Bioinform., 2020

Quantifying the Value of Lateral Views in Deep Learning for Chest X-rays.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

On the limits of cross-domain generalization in automated X-ray prediction.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Uniformizing Techniques to Process CT Scans with 3D CNNs for Tuberculosis Prediction.
Proceedings of the Predictive Intelligence in Medicine - Third International Workshop, 2020

Revisiting Training Strategies and Generalization Performance in Deep Metric Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Is graph biased feature selection of genes better than random?
CoRR, 2019

Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery.
CoRR, 2019

The TCGA Meta-Dataset Clinical Benchmark.
CoRR, 2019

Underwhelming Generalization Improvements From Controlling Feature Attribution.
CoRR, 2019

Torchmeta: A Meta-Learning library for PyTorch.
CoRR, 2019

Analysis of Gene Interaction Graphs for Biasing Machine Learning Models.
CoRR, 2019

Do Lateral Views Help Automated Chest X-ray Predictions?
CoRR, 2019

GradMask: Reduce Overfitting by Regularizing Saliency.
CoRR, 2019

Chester: A Web Delivered Locally Computed Chest X-Ray Disease Prediction System.
CoRR, 2019

Adversarial Domain Adaptation for Stable Brain-Machine Interfaces.
Proceedings of the 7th International Conference on Learning Representations, 2019

Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018
A Survey of Mobile Computing for the Visually Impaired.
CoRR, 2018

Towards the Latent Transcriptome.
CoRR, 2018

Towards Gene Expression Convolutions using Gene Interaction Graphs.
CoRR, 2018

Learning to rank for censored survival data.
CoRR, 2018

Distribution Matching Losses Can Hallucinate Features in Medical Image Translation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2017
Count-ception: Counting by Fully Convolutional Redundant Counting.
CoRR, 2017

ShortScience.org - Reproducing Intuition.
CoRR, 2017

GibbsNet: Iterative Adversarial Inference for Deep Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Count-ception: Counting by Fully Convolutional Redundant Counting.
Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

2016
Academic Torrents: Scalable Data Distribution.
CoRR, 2016

Crater Detection via Convolutional Neural Networks.
CoRR, 2016

RandomOut: Using a convolutional gradient norm to win The Filter Lottery.
CoRR, 2016

Rapid building detection using machine learning.
Appl. Intell., 2016

2015
Semi-Supervised Web Wrapper Repair via Recursive Tree Matching.
CoRR, 2015

The cost of reading research. A study of Computer Science publication venues.
CoRR, 2015

One-Day Activities for K-12 Face-to-Face Outreach.
Proceedings of the 46th ACM Technical Symposium on Computer Science Education, 2015

Prediction gradients for feature extraction and analysis from convolutional neural networks.
Proceedings of the 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, 2015

Spatio-temporal asynchronous co-occurrence pattern for big climate data towards long-lead flood prediction.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014
Comparing semantically-blind and semantically-aware landscape similarity measures with application to query-by-content and regionalization.
Ecol. Informatics, 2014

Academic Torrents: A Community-Maintained Distributed Repository.
Proceedings of the Annual Conference of the Extreme Science and Engineering Discovery Environment, 2014

PASA: Passive broadcast for smartphone ad-hoc networks.
Proceedings of the 23rd International Conference on Computer Communication and Networks, 2014

2013
Wireless Message Dissemination via Selective Relay over Bluetooth (MDSRoB).
CoRR, 2013

2011
Bernoulli trials based feature selection for crater detection.
Proceedings of the 19th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems, 2011

Genetically Enhanced Feature Selection of Discriminative Planetary Crater Image Features.
Proceedings of the AI 2011: Advances in Artificial Intelligence, 2011


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