Matthew B. Blaschko

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 138

Top Venues

Publications

Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang
Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs. CoRR (2024)
Margot Verhulst, Stien Heremans, Matthew B. Blaschko, Ben Somers
Temporal Transferability of Tree Species Classification in Temperate Forests with Sentinel-2 Time Series. Remote. Sens. 16 (14) (2024)
Huy Hoang Nguyen, Matthew B. Blaschko, Simo Saarakkala, Aleksei Tiulpin
Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting From Multimodal Data. IEEE Trans. Medical Imaging 43 (1) (2024)
Mingshi Li, Dusan Grujicic, Steven De Saeger, Stien Heremans, Ben Somers, Matthew B. Blaschko
Biological Valuation Map of Flanders: A Sentinel-2 Imagery Analysis. CoRR (2024)
Omar Hamed, Souhail Bakkali, Marie-Francine Moens, Matthew B. Blaschko, Jordy Van Landeghem
Multimodal Adaptive Inference for Document Image Classification with Anytime Early Exiting. CoRR (2024)
Abhishek Jha, Matthew B. Blaschko, Yuki M. Asano, Tinne Tuytelaars
The Common Stability Mechanism behind most Self-Supervised Learning Approaches. CoRR (2024)
Jiayang Shi, Junyi Zhu, Daniël Maria Pelt, Kees Joost Batenburg, Matthew B. Blaschko
Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction. CoRR (2024)
Chang Tian, Matthew B. Blaschko, Wenpeng Yin, Mingzhe Xing, Yinliang Yue, Marie-Francine Moens
A Generic Method for Fine-grained Category Discovery in Natural Language Texts. CoRR (2024)
Xuefei Ning, Zifu Wang, Shiyao Li, Zinan Lin, Peiran Yao, Tianyu Fu, Matthew B. Blaschko, Guohao Dai, Huazhong Yang, Yu Wang
Can LLMs Learn by Teaching? A Preliminary Study. CoRR (2024)
Jordy Van Landeghem, Sanket Biswas, Matthew B. Blaschko, Marie-Francine Moens
Beyond Document Page Classification: Design, Datasets, and Challenges. WACV (2024)
Jordy Van Landeghem, Subhajit Maity, Ayan Banerjee, Matthew B. Blaschko, Marie-Francine Moens, Josep Lladós, Sanket Biswas
DistilDoc: Knowledge Distillation for Visually-Rich Document Applications. CoRR (2024)
Sinnu Susan Thomas, Guillaume Lamine, Jacopo Palandri, Mohsen Lakehal-Ayat, Punarjay Chakravarty, Friedrich Wolf-Monheim, Matthew B. Blaschko
Mitigating Bias in Bayesian Optimized Data While Designing MacPherson Suspension Architecture. IEEE Trans. Artif. Intell. 5 (2) (2024)
Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Sergey Yekhanin, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better. CoRR (2024)
Junyi Zhu, Zinan Lin, Enshu Liu, Xuefei Ning, Matthew B. Blaschko
Rescaling Intermediate Features Makes Trained Consistency Models Perform Better. Tiny Papers @ ICLR (2024)
Teodora Popordanoska, Sebastian Gregor Gruber, Aleksei Tiulpin, Florian Büttner, Matthew B. Blaschko
Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors. AISTATS (2024)
Teodora Popordanoska, Aleksei Tiulpin, Matthew B. Blaschko
Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection. WACV (2024)
Konstantinos Kontras, Christos Chatzichristos, Matthew B. Blaschko, Maarten De Vos
Improving Multimodal Learning with Multi-Loss Gradient Modulation. CoRR (2024)
Junyi Zhu, Shuochen Liu, Yu Yu, Bo Tang, Yibo Yan, Zhiyu Li, Feiyu Xiong, Tong Xu, Matthew B. Blaschko
FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language Models. CoRR (2024)
Han Zhou, Xingchen Ma, Matthew B. Blaschko
A Corrected Expected Improvement Acquisition Function Under Noisy Observations. CoRR (2023)
Teodora Popordanoska, Gorjan Radevski, Tinne Tuytelaars, Matthew B. Blaschko
Estimating calibration error under label shift without labels. CoRR (2023)
Junyi Zhu, Matthew B. Blaschko
Improving Differentially Private SGD via Randomly Sparsified Gradients. Trans. Mach. Learn. Res. 2023 (2023)
Gorjan Radevski, Dusan Grujicic, Matthew B. Blaschko, Marie-Francine Moens, Tinne Tuytelaars
Multimodal Distillation for Egocentric Action Recognition. ICCV (2023)
Ruben Hemelings, Bart Elen, Alexander K. Schuster, Matthew B. Blaschko, João Barbosa Breda, Pekko Hujanen, Annika Junglas, Stefan Nickels, Andrew White, Norbert Pfeiffer, Paul Mitchell, Patrick De Boever, Anja Tuulonen, Ingeborg Stalmans
A generalizable deep learning regression model for automated glaucoma screening from fundus images. npj Digit. Medicine 6 (2023)
Mingshi Li, Zifu Wang, Matthew B. Blaschko
Improved Imagery Throughput via Cascaded Uncertainty Pruning on U-Net++. NLDL (2023)
Junyi Zhu, Xingchen Ma, Matthew B. Blaschko
Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization. CVPR (2023)
Junyi Zhu, Xingchen Ma, Matthew B. Blaschko
Confidence-aware Personalized Federated Learning via Variational Expectation Maximization. CoRR (2023)
Han Zhou, Xingchen Ma, Matthew B. Blaschko
A Corrected Expected Improvement Acquisition Function Under Noisy Observations. ACML (2023)
Gorjan Radevski, Dusan Grujicic, Marie-Francine Moens, Matthew B. Blaschko, Tinne Tuytelaars
Multimodal Distillation for Egocentric Action Recognition. CoRR (2023)
Zifu Wang, Teodora Popordanoska, Jeroen Bertels, Robin Lemmens, Matthew B. Blaschko
Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels. MICCAI (3) (2023)
Wangduo Xie, Matthew B. Blaschko
Dense Transformer based Enhanced Coding Network for Unsupervised Metal Artifact Reduction. MICCAI (1) (2023)
Jordy Van Landeghem, Sanket Biswas, Matthew B. Blaschko, Marie-Francine Moens
Beyond Document Page Classification: Design, Datasets, and Challenges. CoRR (2023)
Teodora Popordanoska, Aleksei Tiulpin, Matthew B. Blaschko
Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection. CoRR (2023)
Annika Reinke, Minu Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew B. Blaschko, Florian Büttner, M. Jorge Cardoso, Veronika Cheplygina, Jianxu Chen, Evangelia Christodoulou, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Jens Kleesiek, Florian Kofler, Thijs Kooi, Annette Kopp-Schneider, Michal Kozubek, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M. Rafelski, Nasir M. Rajpoot, Mauricio Reyes, Michael A. Riegler, Nicola Rieke, Julio Saez-Rodriguez, Clara I. Sánchez, Shravya Shetty, Maarten van Smeden, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul F. Jäger, Lena Maier-Hein
Understanding metric-related pitfalls in image analysis validation. CoRR (2023)
Wangduo Xie, Matthew B. Blaschko
Dense Transformer based Enhanced Coding Network for Unsupervised Metal Artifact Reduction. CoRR (2023)
Zifu Wang, Matthew B. Blaschko
Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels. CoRR (2023)
Jordy Van Landeghem, Rafal Powalski, Rubèn Tito, Dawid Jurkiewicz, Matthew B. Blaschko, Lukasz Borchmann, Mickaël Coustaty, Sien Moens, Michal Pietruszka, Bertrand Anckaert, Tomasz Stanislawek, Pawel Józiak, Ernest Valveny
Document Understanding Dataset and Evaluation (DUDE). ICCV (2023)
Junyi Zhu, Ruicong Yao, Matthew B. Blaschko
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning. CoRR (2023)
Teodora Popordanoska, Sebastian G. Gruber, Aleksei Tiulpin, Florian Büttner, Matthew B. Blaschko
Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors. CoRR (2023)
Zifu Wang, Xuefei Ning, Matthew B. Blaschko
Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels. NeurIPS (2023)
Zifu Wang, Maxim Berman, Amal Rannen-Triki, Philip H. S. Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko
Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union. NeurIPS (2023)
Zifu Wang, Teodora Popordanoska, Jeroen Bertels, Robin Lemmens, Matthew B. Blaschko
Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels. CoRR (2023)
Sinnu Susan Thomas, Jacopo Palandri, Mohsen Lakehal-Ayat, Punarjay Chakravarty, Friedrich Wolf-Monheim, Matthew B. Blaschko
Kinematics Design of a MacPherson Suspension Architecture Based on Bayesian Optimization. IEEE Trans. Cybern. 53 (4) (2023)
Zifu Wang, Maxim Berman, Amal Rannen Triki, Philip H. S. Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko
Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union. CoRR (2023)
Junyi Zhu, Ruicong Yao, Matthew B. Blaschko
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning. ICML (2023)
Jordy Van Landeghem, Rubèn Tito, Lukasz Borchmann, Michal Pietruszka, Pawel Józiak, Rafal Powalski, Dawid Jurkiewicz, Mickaël Coustaty, Bertrand Anckaert, Ernest Valveny, Matthew B. Blaschko, Sien Moens, Tomasz Stanislawek
Document Understanding Dataset and Evaluation (DUDE). CoRR (2023)
Huy Hoang Nguyen, Matthew B. Blaschko, Simo Saarakkala, Aleksei Tiulpin
Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multimodal Data. CoRR (2022)
Han Zhou, Aida Ashrafi, Matthew B. Blaschko
Combinatorial optimization for low bit-width neural networks. ICPR (2022)
Dusan Grujicic, Matthew B. Blaschko
2-D latent space models: Layer-wise perceptual training and spatial grounding. ICPR (2022)
Sinnu Susan Thomas, Jacopo Palandri, Mohsen Lakehal-Ayat, Punarjay Chakravarty, Friedrich Wolf-Monheim, Matthew B. Blaschko
Designing MacPherson Suspension Architectures using Bayesian Optimization. CoRR (2022)
Zifu Wang, Matthew B. Blaschko
MRF-UNets: Searching UNet with Markov Random Fields. CoRR (2022)
Zifu Wang, Matthew B. Blaschko
MRF-UNets: Searching UNet with Markov Random Fields. ECML/PKDD (3) (2022)
Dusan Grujicic, Thierry Deruyttere, Marie-Francine Moens, Matthew B. Blaschko
Predicting Physical World Destinations for Commands Given to Self-Driving Cars. AAAI (2022)
Teodora Popordanoska, Aleksei Tiulpin, Wacha Bounliphone, Matthew B. Blaschko
On confidence intervals for precision matrices and the eigendecomposition of covariance matrices. CoRR (2022)
Zifu Wang, Matthew B. Blaschko
Optimizing Slimmable Networks for Multiple Target Platforms. NLDL (2022)
Han Zhou, Aida Ashrafi, Matthew B. Blaschko
Combinatorial optimization for low bit-width neural networks. CoRR (2022)
Teodora Popordanoska, Raphael Sayer, Matthew B. Blaschko
A Consistent and Differentiable Lp Canonical Calibration Error Estimator. CoRR (2022)
Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin
CLIMAT: Clinically-Inspired Multi-Agent Transformers for Knee Osteoarthritis Trajectory Forecasting. ISBI (2022)
Thierry Deruyttere, Dusan Grujicic, Matthew B. Blaschko, Marie-Francine Moens
Talk2Car: Predicting Physical Trajectories for Natural Language Commands. IEEE Access 10 (2022)
Teodora Popordanoska, Matthew B. Blaschko
KULeuven at LeQua 2022: Model Calibration in Quantification Learning. CLEF (Working Notes) (2022)
Aleksei Tiulpin, Matthew B. Blaschko
Greedy Bayesian Posterior Approximation with Deep Ensembles. Trans. Mach. Learn. Res. 2022 (2022)
Jordy Van Landeghem, Matthew B. Blaschko, Bertrand Anckaert, Marie-Francine Moens
Benchmarking Scalable Predictive Uncertainty in Text Classification. IEEE Access 10 (2022)
Gorjan Radevski, Dusan Grujicic, Matthew B. Blaschko, Marie-Francine Moens, Tinne Tuytelaars
Students taught by multimodal teachers are superior action recognizers. CoRR (2022)
Teodora Popordanoska, Raphael Sayer, Matthew B. Blaschko
A Consistent and Differentiable Lp Canonical Calibration Error Estimator. NeurIPS (2022)
Xingchen Ma, Matthew B. Blaschko
Meta-Cal: Well-controlled Post-hoc Calibration by Ranking. ICML (2021)
Aleksei Tiulpin, Matthew B. Blaschko
Greedy Bayesian Posterior Approximation with Deep Ensembles. CoRR (2021)
Axel-Jan Rousseau, Thijs Becker, Jeroen Bertels, Matthew B. Blaschko, Dirk Valkenborg
Post Training Uncertainty Calibration Of Deep Networks For Medical Image Segmentation. ISBI (2021)
Xingchen Ma, Matthew B. Blaschko
Additive Tree-Structured Conditional Parameter Spaces in Bayesian Optimization: A Novel Covariance Function and a Fast Implementation. IEEE Trans. Pattern Anal. Mach. Intell. 43 (9) (2021)
Junyi Zhu, Matthew B. Blaschko
Differentially Private SGD with Sparse Gradients. CoRR (2021)
Xingchen Ma, Matthew B. Blaschko
Meta-Cal: Well-controlled Post-hoc Calibration by Ranking. CoRR (2021)
Ruben Hemelings, Bart Elen, João Barbosa Breda, Erwin Bellon, Matthew B. Blaschko, Patrick De Boever, Ingeborg Stalmans
Pointwise visual field estimation from optical coherence tomography in glaucoma: a structure-function analysis using deep learning. CoRR (2021)
Dusan Grujicic, Thierry Deruyttere, Marie-Francine Moens, Matthew B. Blaschko
Predicting Physical World Destinations for Commands Given to Self-Driving Cars. CoRR (2021)
Teodora Popordanoska, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Matthew B. Blaschko
On the Relationship Between Calibrated Predictors and Unbiased Volume Estimation. MICCAI (1) (2021)
Stien Heremans, Francis Turkelboom, Margot Verhulst, Matthew B. Blaschko, Ben Somers
Remote Sensing and Deep Learning for Environmental Policy Support: From Theory to Practice. IGARSS (2021)
Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin
DeepProg: A Transformer-based Framework for Predicting Disease Prognosis. CoRR (2021)
Junyi Zhu, Matthew B. Blaschko
R-GAP: Recursive Gradient Attack on Privacy. ICLR (2021)
Ruben Hemelings, Bart Elen, João Barbosa Breda, Matthew B. Blaschko, Patrick De Boever, Ingeborg Stalmans
Glaucoma detection beyond the optic disc: The importance of the peripapillary region using explainable deep learning. CoRR (2021)
Ruben Hemelings, Bart Elen, Matthew B. Blaschko, Julie Jacob, Ingeborg Stalmans, Patrick De Boever
Pathological myopia classification with simultaneous lesion segmentation using deep learning. Comput. Methods Programs Biomed. 199 (2021)
Teodora Popordanoska, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Matthew B. Blaschko
On the relationship between calibrated predictors and unbiased volume estimation. CoRR (2021)
Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin
Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading From Plain Radiographs. IEEE Trans. Medical Imaging 39 (12) (2020)
Dusan Grujicic, Gorjan Radevski, Tinne Tuytelaars, Matthew B. Blaschko
Learning to ground medical text in a 3D human atlas. CoNLL (2020)
Junyi Zhu, Matthew B. Blaschko
R-GAP: Recursive Gradient Attack on Privacy. CoRR (2020)
Maxim Berman, Leonid Pishchulin, Ning Xu, Matthew B. Blaschko, Gérard G. Medioni
AOWS: Adaptive and Optimal Network Width Search With Latency Constraints. CVPR (2020)
Tom Eelbode, Jeroen Bertels, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko
Optimization for Medical Image Segmentation: Theory and Practice when evaluating with Dice Score or Jaccard Index. CoRR (2020)
Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin
Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading from Plain Radiographs. CoRR (2020)
Maxim Berman, Leonid Pishchulin, Ning Xu, Matthew B. Blaschko, Gérard G. Medioni
AOWS: Adaptive and optimal network width search with latency constraints. CoRR (2020)
Maxim Berman, Matthew B. Blaschko
Discriminative Training of Conditional Random Fields with Probably Submodular Constraints. Int. J. Comput. Vis. 128 (6) (2020)
Ruben Hemelings, Bart Elen, Matthew B. Blaschko, Julie Jacob, Ingeborg Stalmans, Patrick De Boever
Pathological myopia classification with simultaneous lesion segmentation using deep learning. CoRR (2020)
Jiaqian Yu, Matthew B. Blaschko
The Lovász Hinge: A Novel Convex Surrogate for Submodular Losses. IEEE Trans. Pattern Anal. Mach. Intell. 42 (3) (2020)
Tom Eelbode, Jeroen Bertels, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko
Optimization for Medical Image Segmentation: Theory and Practice When Evaluating With Dice Score or Jaccard Index. IEEE Trans. Medical Imaging 39 (11) (2020)
Xingchen Ma, Matthew B. Blaschko
Additive Tree-Structured Conditional Parameter Spaces in Bayesian Optimization: A Novel Covariance Function and a Fast Implementation. CoRR (2020)
Thierry Deruyttere, Simon Vandenhende, Dusan Grujicic, Yu Liu, Luc Van Gool, Matthew B. Blaschko, Tinne Tuytelaars, Marie-Francine Moens
Commands 4 Autonomous Vehicles (C4AV) Workshop Summary. CoRR (2020)
Thierry Deruyttere, Simon Vandenhende, Dusan Grujicic, Yu Liu, Luc Van Gool, Matthew B. Blaschko, Tinne Tuytelaars, Marie-Francine Moens
Commands 4 Autonomous Vehicles (C4AV) Workshop Summary. ECCV Workshops (2) (2020)
Xingchen Ma, Matthew B. Blaschko
Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization. AISTATS (2020)
Xingchen Ma, Matthew B. Blaschko
Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization. CoRR (2020)
Sinnu Susan Thomas, Jacopo Palandri, Mohsen Lakehal-Ayat, Punarjay Chakravarty, Friedrich Wolf-Monheim, Matthew B. Blaschko
Designing MacPherson Suspension Architectures Using Bayesian Optimization. BNAIC/BENELEARN (2019)
Shivangi Srivastava, Maxim Berman, Matthew B. Blaschko, Devis Tuia
Adaptive Compression-based Lifelong Learning. BMVC (2019)
Jeroen Bertels, Tom Eelbode, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko
Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice. CoRR (2019)
Thomas Verelst, Matthew B. Blaschko, Maxim Berman
Generating superpixels using deep image representations. CoRR (2019)
Amal Rannen Triki, Maxim Berman, Vladimir Kolmogorov, Matthew B. Blaschko
Function Norms for Neural Networks. ICCV Workshops (2019)
Ruben Hemelings, Bart Elen, Ingeborg Stalmans, Karel van Keer, Patrick De Boever, Matthew B. Blaschko
Artery-vein segmentation in fundus images using a fully convolutional network. Comput. Medical Imaging Graph. 76 (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Matthew B. Blaschko