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ORCIDEdward De Brouwer
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2020 – today
- 2024
[j4]Michael F. Adamer, Edward De Brouwer, Leslie O'Bray, Bastian Rieck:
The magnitude vector of images. J. Appl. Comput. Topol. 8(3): 447-473 (2024)- [j3]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:
Joint AI-driven event prediction and longitudinal modeling in newly diagnosed and relapsed multiple myeloma. npj Digit. Medicine 7(1) (2024) - [c15]Ilker Demirel, Edward De Brouwer, Zeshan M. Hussain, Michael Oberst, Anthony Philippakis, David A. Sontag:
Benchmarking Observational Studies with Experimental Data under Right-Censoring. AISTATS 2024: 4285-4293 - [c14]Charles Xu, Laney Goldman, Valentina Guo, Benjamin Hollander-Bodie, Maedee Trank-Greene, Ian Adelstein, Edward De Brouwer, Rex Ying, Smita Krishnaswamy, Michael Perlmutter:
BLIS-Net: Classifying and Analyzing Signals on Graphs. AISTATS 2024: 4537-4545 - [c13]Martijn Oldenhof, Edward De Brouwer, Adam Arany, Yves Moreau:
Atom-Level Optical Chemical Structure Recognition with Limited Supervision. CVPR 2024: 17669-17678 - [c12]András Formanek, Edward De Brouwer, Péter Antal, Yves Moreau, Adam Arany:
Model Based Clustering of Time Series Utilizing Expert ODEs. ICANN (4) 2024: 230-245 - [i17]Martijn Oldenhof, Edward De Brouwer, Adam Arany, Yves Moreau:
Atom-Level Optical Chemical Structure Recognition with Limited Supervision. CoRR abs/2404.01743 (2024) - 2023
- [c11]Edward De Brouwer, Rahul G. Krishnan:
Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections. ICLR 2023 - [c10]Martijn Oldenhof, Adam Arany, Yves Moreau, Edward De Brouwer:
Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection. ICLR 2023 - [c9]Dhananjay Bhaskar, Daniel Sumner Magruder, Matheo Morales, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy:
Inferring Dynamic Regulatory Interaction Graphs From Time Series Data With Perturbations. LoG 2023: 22 - [c8]Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy:
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. NeurIPS 2023 - [i16]Edward De Brouwer, Rahul G. Krishnan:
Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections. CoRR abs/2303.01841 (2023) - [i15]Martijn Oldenhof, Adam Arany, Yves Moreau, Edward De Brouwer:
Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection. CoRR abs/2303.05148 (2023) - [i14]Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy:
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. CoRR abs/2305.19043 (2023) - [i13]Dhananjay Bhaskar, Daniel Sumner Magruder, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy:
Inferring dynamic regulatory interaction graphs from time series data with perturbations. CoRR abs/2306.07803 (2023) - [i12]Joyce A. Chew, Edward De Brouwer, Smita Krishnaswamy, Deanna Needell, Michael Perlmutter:
Manifold Filter-Combine Networks. CoRR abs/2307.04056 (2023) - [i11]Charles Xu, Laney Goldman, Valentina Guo, Benjamin Hollander-Bodie, Maedee Trank-Greene, Ian Adelstein, Edward De Brouwer, Rex Ying, Smita Krishnaswamy, Michael Perlmutter:
BLIS-Net: Classifying and Analyzing Signals on Graphs. CoRR abs/2310.17579 (2023) - 2022
- [j2]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:
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]. Comput. Methods Programs Biomed. 213: 106479 (2022) - [c7]Edward De Brouwer, Javier Gonzalez, Stephanie L. Hyland:
Predicting the impact of treatments over time with uncertainty aware neural differential equations. AISTATS 2022: 4705-4722 - [c6]Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt:
Topological Graph Neural Networks. ICLR 2022 - [c5]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:
Augmenting THerapeutic Effectiveness Through Novel Analytics (ATHENA) - A Public and Private Partnership Project Funded by the Flemish Government (VLAIO). MIE 2022: 829-833 - [c4]Edward De Brouwer:
Deep Counterfactual Estimation with Categorical Background Variables. NeurIPS 2022 - [i10]Edward De Brouwer, Javier González Hernández, Stephanie L. Hyland:
Predicting the impact of treatments over time with uncertainty aware neural differential equations. CoRR abs/2202.11987 (2022) - [i9]Edward De Brouwer:
Deep Counterfactual Estimation with Categorical Background Variables. CoRR abs/2210.05811 (2022) - [i8]Yukti Makhija, Edward De Brouwer, Rahul G. Krishnan:
Learning predictive checklists from continuous medical data. CoRR abs/2211.07076 (2022) - 2021
- [j1]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:
Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression. Comput. Methods Programs Biomed. 208: 106180 (2021) - [c3]Edward De Brouwer, Adam Arany, Jaak Simm, Yves Moreau:
Latent Convergent Cross Mapping. ICLR 2021 - [c2]Jaak Simm, Adam Arany, Edward De Brouwer, Yves Moreau:
Expressive Graph Informer Networks. LOD 2021: 198-212 - [i7]Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt:
Topological Graph Neural Networks. CoRR abs/2102.07835 (2021) - [i6]Michael F. Adamer, Leslie O'Bray, Edward De Brouwer, Bastian Rieck, Karsten M. Borgwardt:
The magnitude vector of images. CoRR abs/2110.15188 (2021) - [i5]Jonghyeon Lee, Edward De Brouwer, Boumediene Hamzi, Houman Owhadi:
Learning dynamical systems from data: A simple cross-validation perspective, part III: Irregularly-Sampled Time Series. CoRR abs/2111.13037 (2021) - 2020
- [i4]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:
Longitudinal modeling of MS patient trajectories improves predictions of disability progression. CoRR abs/2011.04749 (2020)
2010 – 2019
- 2019
- [c1]Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau:
GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series. NeurIPS 2019: 7377-7388 - [i3]Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau:
GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series. CoRR abs/1905.12374 (2019) - [i2]Jaak Simm, Adam Arany, Edward De Brouwer, Yves Moreau:
Graph Informer Networks for Molecules. CoRR abs/1907.11318 (2019) - 2018
- [i1]Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau:
Deep Ensemble Tensor Factorization for Longitudinal Patient Trajectories Classification. CoRR abs/1811.10501 (2018)
Coauthor Index
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last updated on 2024-10-08 21:33 CEST by the dblp team
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