Boris Joukovsky

According to our database, Boris Joukovsky authored at least 15 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

SNIPPET: A Framework for Subjective Evaluation of Visual Explanations Applied to DeepFake Detection.

Yuqing Yang, Boris Joukovsky, José Oramas Mogrovejo, Tinne Tuytelaars, Nikos Deligiannis

ACM Trans. Multim. Comput. Commun. Appl., August, 2024

Visualizing and Understanding Contrastive Learning.

Fawaz Sammani, Boris Joukovsky, Nikos Deligiannis

IEEE Trans. Image Process., 2024

Learned Layered Coding for Successive Refinement in the Wyner-Ziv Problem.

Boris Joukovsky, Brent De Weerdt, Nikos Deligiannis

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Model-Agnostic Visual Explanations via Approximate Bilinear Models.

Boris Joukovsky, Fawaz Sammani, Nikos Deligiannis

Proceedings of the IEEE International Conference on Image Processing, 2023

Visualizing Invariant Features in Vision Models.

Fawaz Sammani, Boris Joukovsky, Nikos Deligiannis

Proceedings of the 24th International Conference on Digital Signal Processing, 2023

Relevance Propagation through Deep Conditional Random Fields.

Xiangyu Yang, Boris Joukovsky, Nikos Deligiannis

Proceedings of the IEEE International Conference on Acoustics, 2023

Quantitative Evaluation of Video Explainability Methods via Anomaly Localization.

Xinyue Zhang, Boris Joukovsky, Nikos Deligiannis

Proceedings of the 31st European Signal Processing Conference, 2023

2022

Visualizing and Understanding Self-Supervised Vision Learning.

Fawaz Sammani, Boris Joukovsky, Nikos Deligiannis

CoRR, 2022

FRF estimation using multiple kernel-based regularisation.

Noël Hallemans, Rik Pintelon, Boris Joukovsky, Dries Peumans, John Lataire

Autom., 2022

2021

reweighted-RNN: An Interpretable Recurrent Neural Network for Video Reconstruction via Deep Unfolding.

Boris Joukovsky, Huynh Van Luong, Nikos Deligiannis

Dataset, April, 2021

Designing Interpretable Recurrent Neural Networks for Video Reconstruction via Deep Unfolding.

Huynh Van Luong, Boris Joukovsky, Nikos Deligiannis

IEEE Trans. Image Process., 2021

Generalization error bounds for deep unfolding RNNs.

Boris Joukovsky, Tanmoy Mukherjee, Huynh Van Luong, Nikos Deligiannis

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging.

Abel Díaz Berenguer, Hichem Sahli, Boris Joukovsky, Maryna Kvasnytsia, Ine Dirks, Mitchel Alioscha-Pérez, Nikos Deligiannis, Panagiotis Gonidakis, Sebastián Amador Sánchez, Redona Brahimetaj, Evgenia Papavasileiou, Jonathan Cheung-Wai Chan, Fei Li, Shangzhen Song, Yixin Yang, Sofie Tilborghs, Siri Willems, Tom Eelbode, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Paul Suetens, Lucas Fidon, Tom Vercauteren, David Robben, Arne Brys, Dirk Smeets, Bart Ilsen, Nico Buls, Nina Watté, Johan de Mey, Annemiek Snoeckx, Paul M. Parizel, Julien Guiot, Louis Deprez, Paul Meunier, Stefaan Gryspeerdt, Kristof De Smet, Bart Jansen, Jef Vandemeulebroucke

CoRR, 2020

Interpretable Deep Recurrent Neural Networks via Unfolding Reweighted 𝓁₁-𝓁₁ Minimization: Architecture Design and Generalization Analysis.

Huynh Van Luong, Boris Joukovsky, Nikos Deligiannis

CoRR, 2020

A Deep-Unfolded Reference-Based RPCA Network For Video Foreground-Background Separation.

Huynh Van Luong, Boris Joukovsky, Yonina C. Eldar, Nikos Deligiannis

Proceedings of the 28th European Signal Processing Conference, 2020