Hossein Azizpour

CoRR, 2024

2023

Deep Double Descent via Smooth Interpolation.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Logistic-Normal Likelihoods for Heteroscedastic Label Noise in Classification.

[BibT_eX]

[DOI]

Amir Mehrpanah

CoRR, 2023

PatchDropout: Economizing Vision Transformers Using Patch Dropout.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Miquel Martí i Rabadán

Alessandro Pieropan

Theodoros Panagiotakopoulos

Atsuto Maki

Proceedings of the 2023 Northern Lights Deep Learning Workshop, 2023

To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation.

[BibT_eX]

[DOI]

Marc Botet Colomer

Pier Luigi Dovesi

Joao Frederico Carvalho

Linus Härenstam-Nielsen

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

On the Lipschitz Constant of Deep Networks and Double Descent.

[BibT_eX]

[DOI]

Matteo Gamba

Mårten Björkman

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022

In Memoriam: Jan-Olof Eklundh.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Sentinel-1 and Sentinel-2 Data Fusion for Urban Change Detection Using a Dual Stream U-Net.

[BibT_eX]

[DOI]

IEEE Geosci. Remote. Sens. Lett., 2022

Unsupervised Flood Detection on SAR Time Series.

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

CoRR, 2022

Learnable Masked Tokens for Improved Transferability of Self-supervised Vision Transformers.

[BibT_eX]

[DOI]

Hao Hu

Adrian Chmielewski-Anders

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

An analysis of over-sampling labeled data in semi-supervised learning with FixMatch.

[BibT_eX]

[DOI]

Proceedings of the 2022 Northern Lights Deep Learning Workshop, 2022

Are All Linear Regions Created Equal?

[BibT_eX]

[DOI]

Matteo Gamba

Josephine Sullivan

Mårten Björkman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Consistency Regularization Can Improve Robustness to Label Noise.

[BibT_eX]

[DOI]

CoRR, 2021

GraphQA: protein model quality assessment using graph convolutional networks.

[BibT_eX]

[DOI]

David Menéndez Hurtado

Arne Elofsson

Bioinform., 2021

CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

CoRR, 2020

Hyperplane Arrangements of Trained ConvNets Are Biased.

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

Decoupling Inherent Risk and Early Cancer Signs in Image-Based Breast Cancer Risk Models.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Explanation-Based Weakly-Supervised Learning of Visual Relations with Graph Networks.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Efficient Evaluation-Time Uncertainty Estimation by Improved Distillation.

[BibT_eX]

[DOI]

CoRR, 2019

Explainability Techniques for Graph Convolutional Networks.

[BibT_eX]

[DOI]

CoRR, 2019

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

[BibT_eX]

[DOI]

Francesco Fuso Nerini

CoRR, 2019

On the Geometry of Rectifier Convolutional Neural Networks.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

CoRR, 2018

Bayesian Uncertainty Estimation for Batch Normalized Deep Networks.

[BibT_eX]

[DOI]

Mattias Teye

Kevin Smith

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

The Preimage of Rectifier Network Activities.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Visual Representations and Models: From Latent SVM to Deep Learning.

[BibT_eX]

[DOI]

PhD thesis, 2016

Factors of Transferability for a Generic ConvNet Representation.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2016

2015

Persistent Evidence of Local Image Properties in Generic ConvNets.

[BibT_eX]

[DOI]

Proceedings of the Image Analysis - 19th Scandinavian Conference, 2015

From generic to specific deep representations for visual recognition.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2015

Spotlight the Negatives: A Generalized Discriminative Latent Model.

[BibT_eX]

[DOI]

Proceedings of the British Machine Vision Conference 2015, 2015

2014

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

[BibT_eX]

[DOI]

Stefan Carlsson

CoRR, 2014

CNN Features Off-the-Shelf: An Astounding Baseline for Recognition.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013

Multi-view Body Part Recognition with Random Forests.

[BibT_eX]

[DOI]

Proceedings of the British Machine Vision Conference, 2013

2012

Object Detection Using Strongly-Supervised Deformable Part Models.

[BibT_eX]

[DOI]