Edward De Brouwer

According to our database, Edward De Brouwer authored at least 29 papers between 2018 and 2024.

Collaborative distances:

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

2024

The magnitude vector of images.

Michael F. Adamer, Edward De Brouwer, Leslie O'Bray, Bastian Rieck

J. Appl. Comput. Topol., September, 2024

Joint AI-driven event prediction and longitudinal modeling in newly diagnosed and relapsed multiple myeloma.

Zeshan M. Hussain, Edward De Brouwer, Rebecca Boiarsky, Sama Setty, Neeraj Gupta, Guohui Liu, Cong Li, Jaydeep Srimani, Jacob Zhang, Rich Labotka, David A. Sontag

npj Digit. Medicine, 2024

Convergence of Manifold Filter-Combine Networks.

David R. Johnson, Joyce A. Chew, Siddharth Viswanath, Edward De Brouwer, Deanna Needell, Smita Krishnaswamy, Michael Perlmutter

CoRR, 2024

Model Based Clustering of Time Series Utilizing Expert ODEs.

András Formanek, Edward De Brouwer, Péter Antal, Yves Moreau, Adam Arany

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

Atom-Level Optical Chemical Structure Recognition with Limited Supervision.

Martijn Oldenhof, Edward De Brouwer, Adam Arany, Yves Moreau

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Benchmarking Observational Studies with Experimental Data under Right-Censoring.

Ilker Demirel, Edward De Brouwer, Zeshan M. Hussain, Michael Oberst, Anthony Philippakis, David A. Sontag

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

BLIS-Net: Classifying and Analyzing Signals on Graphs.

Charles Xu, Laney Goldman, Valentina Guo, Benjamin Hollander-Bodie, Maedee Trank-Greene, Ian Adelstein, Edward De Brouwer, Rex Ying, Smita Krishnaswamy, Michael Perlmutter

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Manifold Filter-Combine Networks.

Joyce A. Chew, Edward De Brouwer, Smita Krishnaswamy, Deanna Needell, Michael Perlmutter

CoRR, 2023

Inferring dynamic regulatory interaction graphs from time series data with perturbations.

Dhananjay Bhaskar, Daniel Sumner Magruder, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy

CoRR, 2023

A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction.

Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Inferring Dynamic Regulatory Interaction Graphs From Time Series Data With Perturbations.

Dhananjay Bhaskar, Daniel Sumner Magruder, Matheo Morales, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy

Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection.

Martijn Oldenhof, Adam Arany, Yves Moreau, Edward De Brouwer

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections.

Edward De Brouwer, Rahul G. Krishnan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Learning predictive checklists from continuous medical data.

Yukti Makhija, Edward De Brouwer, Rahul G. Krishnan

CoRR, 2022

Predicting the impact of treatments over time with uncertainty aware neural differential equations.

Edward De Brouwer, Javier González Hernández, Stephanie L. Hyland

CoRR, 2022

Corrigendum to Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression: [Computer Methods and Programs in Biomedicine, Volume 208, (September 2021) 106180].

Edward De Brouwer, Thijs Becker, Yves Moreau, Eva Kubala Havrdova, Maria Trojano, Sara Eichau, Serkan Ozakbas, Marco Onofrj, Pierre Grammond, Jens Kuhle, Ludwig Kappos, Patrizia Sola, Elisabetta Cartechini, Jeannette Lechner-Scott, Raed Alroughani, Oliver Gerlach, Tomas Kalincik, Franco Granella, Francois Grand'Maison, Roberto Bergamaschi, Maria Jose Sa, Bart Van Wijmeersch, Aysun Soysal, Jose Luis Sanchez-Menoyo, Claudio Solaro, Cavit Boz, Gerardo Iuliano, Katherine Buzzard, Eduardo Aguera-Morales, Murat Terzi, Tamara Castillo Trivio, Daniele Spitaleri, Vincent Van Pesch, Vahid Shaygannejad, Fraser Moore, Celia Oreja Guevara, Davide Maimone, Riadh Gouider, Tunde Csepany, Cristina Ramo-Tello, Liesbet M. Peeters

Comput. Methods Programs Biomed., 2022

Deep Counterfactual Estimation with Categorical Background Variables.

Edward De Brouwer

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Augmenting THerapeutic Effectiveness Through Novel Analytics (ATHENA) - A Public and Private Partnership Project Funded by the Flemish Government (VLAIO).

Ploingarm Petsophonsakul, Ashkan Pirmani, Edward De Brouwer, Murat Akand, Wouter Botermans, Frank Van Der Aa, Joris Robert Vermeesch, Fritz Offner, Roel Wuyts, Yves Moreau, Ingrid Maes, Ines Blockx, Patricia Van Rompuy, Martine Lewi, Bart Vannieuwenhuyse

Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022

Topological Graph Neural Networks.

Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt

Proceedings of the Tenth International Conference on Learning Representations, 2022

Predicting the impact of treatments over time with uncertainty aware neural differential equations.

Edward De Brouwer, Javier Gonzalez, Stephanie L. Hyland

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

2021

Learning dynamical systems from data: A simple cross-validation perspective, part III: Irregularly-Sampled Time Series.

Jonghyeon Lee, Edward De Brouwer, Boumediene Hamzi, Houman Owhadi

CoRR, 2021

The magnitude vector of images.

Michael F. Adamer, Leslie O'Bray, Edward De Brouwer, Bastian Rieck, Karsten M. Borgwardt

CoRR, 2021

Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression.

Edward De Brouwer, Thijs Becker, Yves Moreau, Eva Kubala Havrdova, Maria Trojano, Sara Eichau, Serkan Ozakbas, Marco Onofrj, Pierre Grammond, Jens Kuhle, Ludwig Kappos, Patrizia Sola, Elisabetta Cartechini, Jeannette Lechner-Scott, Raed Alroughani, Oliver Gerlach, Tomas Kalincik, Franco Granella, Francois Grand'Maison, Roberto Bergamaschi, Maria Jose Sa, Bart Van Wijmeersch, Aysun Soysal, Jose Luis Sanchez-Menoyo, Claudio Solaro, Cavit Boz, Gerardo Iuliano, Katherine Buzzard, Eduardo Aguera-Morales, Murat Terzi, Tamara Castillo Trivio, Daniele Spitaleri, Vincent Van Pesch, Vahid Shaygannejad, Fraser Moore, Celia Oreja Guevara, Davide Maimone, Riadh Gouider, Tunde Csepany, Cristina Ramo-Tello, Liesbet M. Peeters

Comput. Methods Programs Biomed., 2021

Expressive Graph Informer Networks.

Jaak Simm, Adam Arany, Edward De Brouwer, Yves Moreau

Proceedings of the Machine Learning, Optimization, and Data Science, 2021

Latent Convergent Cross Mapping.

Edward De Brouwer, Adam Arany, Jaak Simm, Yves Moreau

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Longitudinal modeling of MS patient trajectories improves predictions of disability progression.

Edward De Brouwer, Thijs Becker, Yves Moreau, Eva Kubala Havrdova, Maria Trojano, Sara Eichau, Serkan Ozakbas, Marco Onofrj, Pierre Grammond, Jens Kuhle, Ludwig Kappos, Patrizia Sola, Elisabetta Cartechini, Jeannette Lechner-Scott, Raed Alroughani, Oliver Gerlach, Tomas Kalincik, Franco Granella, Francois Grand'Maison, Roberto Bergamaschi, Maria Jose Sa, Bart Van Wijmeersch, Aysun Soysal, Jose Luis Sanchez-Menoyo, Claudio Solaro, Cavit Boz, Gerardo Iuliano, Katherine Buzzard, Eduardo Aguera-Morales, Murat Terzi, Tamara Castillo Trivio, Daniele Spitaleri, Vincent Van Pesch, Vahid Shaygannej, Fraser Moore, Celia Oreja Guevara, Davide Maimone, Riadh Gouider, Tunde Csepany, Cristina Ramo-Tello, Liesbet M. Peeters

CoRR, 2020

2019

Graph Informer Networks for Molecules.

Jaak Simm, Adam Arany, Edward De Brouwer, Yves Moreau

CoRR, 2019

GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series.

Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Deep Ensemble Tensor Factorization for Longitudinal Patient Trajectories Classification.

Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau

CoRR, 2018