Hossein Azizpour

Orcid: 0000-0001-5211-6388

According to our database1, Hossein Azizpour authored at least 52 papers between 2012 and 2024.

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

Timeline

Legend:

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Bibliography

2024
Unsupervised flood detection on SAR time series using variational autoencoder.
Int. J. Appl. Earth Obs. Geoinformation, February, 2024

Hessian-Informed Flow Matching.
CoRR, 2024

Medical Image Segmentation with SAM-generated Annotations.
CoRR, 2024

Inverse Problems with Diffusion Models: A MAP Estimation Perspective.
CoRR, 2024

Revisiting Score Function Estimators for <i>k</i>-Subset Sampling.
CoRR, 2024

Continuous Urban Change Detection from Satellite Image Time Series with Temporal Feature Refinement and Multi-Task Integration.
CoRR, 2024

Opportunities for machine learning in scientific discovery.
CoRR, 2024

Stable Autonomous Flow Matching.
CoRR, 2024

Indirectly Parameterized Concrete Autoencoders.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Robust Classification via Regression for Learning with Noisy Labels.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

On Spectral Properties of Gradient-Based Explanation Methods.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
Deep Double Descent via Smooth Interpolation.
Trans. Mach. Learn. Res., 2023

Logistic-Normal Likelihoods for Heteroscedastic Label Noise.
Trans. Mach. Learn. Res., 2023

Logistic-Normal Likelihoods for Heteroscedastic Label Noise in Classification.
CoRR, 2023

PatchDropout: Economizing Vision Transformers Using Patch Dropout.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Dense FixMatch: a simple semi-supervised learning method for pixel-wise prediction tasks.
Proceedings of the 2023 Northern Lights Deep Learning Workshop, 2023

To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

On the Lipschitz Constant of Deep Networks and Double Descent.
Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022
In Memoriam: Jan-Olof Eklundh.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Sentinel-1 and Sentinel-2 Data Fusion for Urban Change Detection Using a Dual Stream U-Net.
IEEE Geosci. Remote. Sens. Lett., 2022

Unsupervised Flood Detection on SAR Time Series.
CoRR, 2022

Towards Self-Supervised Learning of Global and Object-Centric Representations.
CoRR, 2022

The potential of artificial intelligence for achieving healthy and sustainable societies.
CoRR, 2022

Learnable Masked Tokens for Improved Transferability of Self-supervised Vision Transformers.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

An analysis of over-sampling labeled data in semi-supervised learning with FixMatch.
Proceedings of the 2022 Northern Lights Deep Learning Workshop, 2022

Are All Linear Regions Created Equal?
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Consistency Regularization Can Improve Robustness to Label Noise.
CoRR, 2021

GraphQA: protein model quality assessment using graph convolutional networks.
Bioinform., 2021

CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Recurrent neural networks and Koopman-based frameworks for temporal predictions in turbulence.
CoRR, 2020

Hyperplane Arrangements of Trained ConvNets Are Biased.
CoRR, 2020

On the use of recurrent neural networks for predictions of turbulent flows.
CoRR, 2020

Decoupling Inherent Risk and Early Cancer Signs in Image-Based Breast Cancer Risk Models.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Explanation-Based Weakly-Supervised Learning of Visual Relations with Graph Networks.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Efficient Evaluation-Time Uncertainty Estimation by Improved Distillation.
CoRR, 2019

Explainability Techniques for Graph Convolutional Networks.
CoRR, 2019

The role of artificial intelligence in achieving the Sustainable Development Goals.
CoRR, 2019

On the Geometry of Rectifier Convolutional Neural Networks.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018
GANtruth - an unpaired image-to-image translation method for driving scenarios.
CoRR, 2018

Bayesian Uncertainty Estimation for Batch Normalized Deep Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
The Preimage of Rectifier Network Activities.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Visual Representations and Models: From Latent SVM to Deep Learning.
PhD thesis, 2016

Factors of Transferability for a Generic ConvNet Representation.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

2015
Persistent Evidence of Local Image Properties in Generic ConvNets.
Proceedings of the Image Analysis - 19th Scandinavian Conference, 2015

From generic to specific deep representations for visual recognition.
Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2015

Spotlight the Negatives: A Generalized Discriminative Latent Model.
Proceedings of the British Machine Vision Conference 2015, 2015

2014
Self-tuned Visual Subclass Learning with Shared Samples An Incremental Approach.
CoRR, 2014

CNN Features Off-the-Shelf: An Astounding Baseline for Recognition.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Multi-view Body Part Recognition with Random Forests.
Proceedings of the British Machine Vision Conference, 2013

2012
Object Detection Using Strongly-Supervised Deformable Part Models.
Proceedings of the Computer Vision - ECCV 2012, 2012

Mixture Component Identification and Learning for Visual Recognition.
Proceedings of the Computer Vision - ECCV 2012, 2012


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