Algebraic C*-actions and the inverse kinematics of a general 6R manipulator. - Sandra Di Rocco; David Eklund; Andrew J. Sommese; Charles W. Wampler (Appl. Math. Comput., 2010)

Chern numbers of smooth varieties via homotopy continuation and intersection theory. - Sandra Di Rocco; David Eklund; Chris Peterson 001; Andrew J. Sommese (J. Symb. Comput., 2011)

Computing intersection numbers of Chern classes. - Daniel J. Bates; David Eklund; Chris Peterson 001 (J. Symb. Comput., 2013)

Perturbed homotopies for finding all isolated solutions of polynomial systems. - Daniel J. Bates; Brent R. Davis; David Eklund; Eric M. Hanson; Chris Peterson 001 (Appl. Math. Comput., 2014)

Numerical polar calculus and cohomology of line bundles. - Sandra Di Rocco; David Eklund; Chris Peterson 001 (Adv. Appl. Math., 2018)

Expected path length on random manifolds. - David Eklund; Søren Hauberg (CoRR, 2019)

Variational Autoencoders with Riemannian Brownian Motion Priors. - Dimitrios Kalatzis; David Eklund; Georgios Arvanitidis; Søren Hauberg (ICML, 2020)

The Bottleneck Degree of Algebraic Varieties. - Sandra Di Rocco; David Eklund; Madeleine Weinstein (SIAM J. Appl. Algebra Geom., 2020)

Excess intersections and numerical irreducible decompositions. - Daniel J. Bates; David Eklund; Jonathan D. Hauenstein; Chris Peterson 001 (SYNASC, 2021)

Non-IID data re-balancing at IoT edge with peer-to-peer federated learning for anomaly detection. - Han Wang 031; Luis Muñoz-González; David Eklund; Shahid Raza (WISEC, 2021)

Sampling and homology via bottlenecks. - Sandra Di Rocco; David Eklund; Oliver Gäfvert (Math. Comput., 2022)

Privacy-preserving Federated Learning System for Fatigue Detection. - Mohammadreza Mohammadi; Roberto Allocca; David Eklund; Rakesh Shrestha; Sima Sinaei (CSR, 2023)

The numerical algebraic geometry of bottlenecks. - David Eklund (Adv. Appl. Math., 2023)

Identifying latent distances with Finslerian geometry. - Alison Pouplin; David Eklund; Carl Henrik Ek; Søren Hauberg (Trans. Mach. Learn. Res., 2023)

SparSFA: Towards robust and communication-efficient peer-to-peer federated learning. - Han Wang 031; Luis Muñoz-González; Muhammad Zaid Hameed; David Eklund; Shahid Raza (Comput. Secur., 2023)

FL4IoT: IoT Device Fingerprinting and Identification Using Federated Learning. - Han Wang 031; David Eklund; Alina Oprea; Shahid Raza (ACM Trans. Internet Things, 2023)

Computing Geometric Feature Sizes for Algebraic Manifolds. - Sandra Di Rocco; Parker B. Edwards; David Eklund; Oliver Gäfvert; Jonathan D. Hauenstein (SIAM J. Appl. Algebra Geom., 2023)

PRIV-DRIVE: Privacy-Ensured Federated Learning using Homomorphic Encryption for Driver Fatigue Detection. - Sima Sinaei; Mohammadreza Mohammadi; Rakesh Shrestha; Mina Alibeigi; David Eklund (DSD, 2024)

BMI: Bounded Mutual Information for Efficient Privacy-Preserving Feature Selection. - David Eklund; Alfonso Iacovazzi; Han Wang 031; Apostolos Pyrgelis; Shahid Raza (ESORICS (2), 2024)

Certifying Robustness via Topological Representations. - Jens Agerberg; Andrea Guidolin; Andrea Martinelli; Pepijn Roos Hoefgeest; David Eklund; Martina Scolamiero (CoRR, 2025)