De Brouwer, Edward

19 publications

ICLR 2025 Modeling Complex System Dynamics with Flow Matching Across Time and Conditions Martin Rohbeck, Edward De Brouwer, Charlotte Bunne, Jan-Christian Huetter, Anne Biton, Kelvin Y. Chen, Aviv Regev, Romain Lopez

ICLRW 2025 RAG-Enhanced Collaborative LLM Agents for Drug Discovery Namkyeong Lee, Edward De Brouwer, Ehsan Hajiramezanali, Tommaso Biancalani, Chanyoung Park, Gabriele Scalia

CVPR 2024 Atom-Level Optical Chemical Structure Recognition with Limited Supervision Martijn Oldenhof, Edward De Brouwer, Adam Arany, Yves Moreau

AISTATS 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

AISTATS 2024 Benchmarking Observational Studies with Experimental Data Under Right-Censoring Ilker Demirel, Edward De Brouwer, Zeshan M Hussain, Michael Oberst, Anthony A Philippakis, David Sontag

NeurIPSW 2024 Convergence of Manifold Filter-Combine Networks David R Johnson, Joyce Chew, Siddharth Viswanath, Edward De Brouwer, Deanna Needell, Smita Krishnaswamy, Michael Perlmutter

NeurIPSW 2024 Learning Multi-Cellular Representations of Single-Cell Transcriptomics Data Enables Characterization of Patient-Level Disease States Tianyu Liu, Edward De Brouwer, Tony Kuo, Nathaniel Lee Diamant, Missarova Alsu, Minsheng Hao, Hanchen, Hector Corrada Bravo, Gabriele Scalia, Aviv Regev, Graham Heimberg

NeurIPSW 2024 Modeling Complex System Dynamics with Flow Matching Across Time and Conditions Martin Rohbeck, Charlotte Bunne, Edward De Brouwer, Jan-Christian Huetter, Anne Biton, Kelvin Y. Chen, Aviv Regev, Romain Lopez

NeurIPS 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

ICMLW 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

ICLR 2023 Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections Edward De Brouwer, Rahul G Krishnan

LoG 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, James Noonan, Guy Wolf, Natalia Ivanova, Smita Krishnaswamy

ICLR 2023 Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection Martijn Oldenhof, Adam Arany, Yves Moreau, Edward De Brouwer

AISTATS 2022 Predicting the Impact of Treatments over Time with Uncertainty Aware Neural Differential Equations. Edward De Brouwer, Javier Gonzalez, Stephanie Hyland

NeurIPS 2022 Deep Counterfactual Estimation with Categorical Background Variables Edward De Brouwer

ICLR 2022 Topological Graph Neural Networks Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten Borgwardt

ICLR 2021 Latent Convergent Cross Mapping Edward De Brouwer, Adam Arany, Jaak Simm, Yves Moreau

ICMLW 2020 Inferring Causal Dependencies Between Chaotic Dynamical Systems from Sporadic Time Series Edward De Brouwer, Adam Arany, Jaak Simm, Yves Moreau

NeurIPS 2019 GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau