Bubacarr Bah

According to our database, Bubacarr Bah authored at least 30 papers between 2010 and 2024.

Collaborative distances:

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

2024

Recent methodological advances in federated learning for healthcare.

Fan Zhang, Daniel Kreuter, Yichen Chen, Sören Dittmer, Samuel Tull, Tolou Shadbahr, Martijn Schut, Folkert W. Asselbergs, Sujoy Kar, Suthesh Sivapalaratnam, Sophie Williams, Mickey Koh, Yvonne Henskens, Bart de Wit, Umberto D'alessandro, Bubacarr Bah, Ousman Secka, Parashkev Nachev, Rajeev Gupta, Sara Trompeter, Nancy Boeckx, Christine van Laer, Gordon A. Awandare, Kwabena Sarpong, Lucas Amenga-Etego, Mathie Leers, Mirelle Huijskens, Samuel McDermott, Willem H. Ouwehand, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts

Patterns, 2024

Physics-informed neural networks for Timoshenko system with Thermoelasticity.

Sabrine Chebbi, Joseph Muthui Wacira, Makram Hamouda, Bubacarr Bah

CoRR, 2024

This Actually Looks Like that: Proto-BagNets for Local and Global Interpretability-by-Design.

Kerol Djoumessi, Bubacarr Bah, Laura Kühlewein, Philipp Berens, Lisa M. Koch

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

2023

Improved identification accuracy in equation learning via comprehensive R2-elimination and Bayesian model selection.

Daniel Nickelsen, Bubacarr Bah

Trans. Mach. Learn. Res., 2023

Improved identification accuracy in equation learning via comprehensive R²-elimination and Bayesian model selection.

Daniel Nickelsen, Bubacarr Bah

CoRR, 2023

A physics-informed neural network framework for modeling obstacle-related equations.

Hamid El Bahja, Jan Christian Hauffen, Peter Jung, Bubacarr Bah, Issa Karambal

CoRR, 2023

Sparse Activations for Interpretable Disease Grading.

Kerol R. Djoumessi Donteu, Indu Ilanchezian, Laura Kühlewein, Hanna Faber, Christian F. Baumgartner, Bubacarr Bah, Philipp Berens, Lisa M. Koch

Proceedings of the Medical Imaging with Deep Learning, 2023

2021

Discrete optimization methods for group model selection in compressed sensing.

Bubacarr Bah, Jannis Kurtz, Oliver Schaudt

Math. Program., 2021

Efficient and Robust Mixed-Integer Optimization Methods for Training Binarized Deep Neural Networks.

Jannis Kurtz, Bubacarr Bah

CoRR, 2021

Towards the Localisation of Lesions in Diabetic Retinopathy.

Samuel Ofosu Mensah, Bubacarr Bah, Willie Brink

Proceedings of the Intelligent Computing, 2021

Low Rank Matrix Approximation for Imputing Missing Categorical Data.

Joseph Muthui Wacira, Dinna Ranirina, Bubacarr Bah

Proceedings of the Artificial Intelligence Research - Second Southern African Conference, 2021

Improving the Reliability of Pooled Testing with Combinatorial Decoding and Compressed Sensing.

Hendrik Bernd Petersen, Shankar Agarwal, Peter Jung, Bubacarr Bah

Proceedings of the 55th Annual Conference on Information Sciences and Systems, 2021

2020

Editorial: Recent Developments in Signal Approximation and Reconstruction.

Bubacarr Bah, Jean-Luc Bouchot

Frontiers Appl. Math. Stat., 2020

Practical High-Throughput, Non-Adaptive and Noise-Robust SARS-CoV-2 Testing.

Hendrik Bernd Petersen, Bubacarr Bah, Peter Jung

CoRR, 2020

An Integer Programming Approach to Deep Neural Networks with Binary Activation Functions.

Bubacarr Bah, Jannis Kurtz

CoRR, 2020

Efficient Noise-Blind 𝓁₁-Regression of Nonnegative Compressible Signals.

Hendrik Bernd Petersen, Bubacarr Bah, Peter Jung

CoRR, 2020

On Error Correction Neural Networks for Economic Forecasting.

Mhlasakululeka Mvubu, Emmanuel Kabuga, Christian Plitz, Bubacarr Bah, Ronnie Becker, Hans-Georg Zimmermann

Proceedings of the IEEE 23rd International Conference on Information Fusion, 2020

2019

Learning deep linear neural networks: Riemannian gradient flows and convergence to global minimizers.

Bubacarr Bah, Holger Rauhut, Ulrich Terstiege, Michael Westdickenberg

CoRR, 2019

Outcome prediction with serial neuron-specific enolase and machine learning in anoxic-ischaemic disorders of consciousness.

Emily Muller, Jonathan P. Shock, Andreas Bender, Julian Kleeberger, Tobias Högen, Martin Justinus Rosenfelder, Bubacarr Bah, Alex Lopez-Rolon

Comput. Biol. Medicine, 2019

2018

On the Construction of Sparse Matrices From Expander Graphs.

Bubacarr Bah, Jared Tanner

Frontiers Appl. Math. Stat., 2018

2016

The Sample Complexity of Weighted Sparse Approximation.

Bubacarr Bah, Rachel A. Ward

IEEE Trans. Signal Process., 2016

Weighted sparse recovery with expanders.

Bubacarr Bah

CoRR, 2016

Convex Block-sparse Linear Regression with Expanders - Provably.

Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2014

Model-based Sketching and Recovery with Expanders.

Bubacarr Bah, Luca Baldassarre, Volkan Cevher

Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

Metric learning with rank and sparsity constraints.

Bubacarr Bah, Stephen Becker, Volkan Cevher, Baran Gozcu

Proceedings of the IEEE International Conference on Acoustics, 2014

2013

Vanishingly Sparse Matrices and Expander Graphs, With Application to Compressed Sensing.

Bubacarr Bah, Jared Tanner

IEEE Trans. Inf. Theory, 2013

On construction and analysis of sparse random matrices and expander graphs with applications to compressed sensing.

Bubacarr Bah, Jared Tanner

CoRR, 2013

Energy-aware adaptive bi-Lipschitz embeddings.

Bubacarr Bah, Ali Sadeghian, Volkan Cevher

CoRR, 2013

2012

Bounds of restricted isometry constants in extreme asymptotics: formulae for Gaussian matrices

Bubacarr Bah, Jared Tanner

CoRR, 2012

2010

Improved Bounds on Restricted Isometry Constants for Gaussian Matrices.

Bubacarr Bah, Jared Tanner

SIAM J. Matrix Anal. Appl., 2010