Author

Santiago Segarra

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#machine learning Preprint Sep 2026

Feasible Flow Matching for Graph Reconstruction via Within-Sampling Primal-Dual Guidance

Constrained Primal-Dual PIFM (CPD-PIFM), which augments the sampler with Lagrange multipliers that evolve along each trajectory, raises feasibility by 11-26 percentage points and remains competitive with fixed guidance without selecting a separate multiplier for each constraint.

Hao-Ming Chen, Nicolas Zilberstein, Santiago Paternain et al. · 0 citations

Preprint Sep 2026

Biased Backpressure Routing for Multihop Wireless Networks with Heterogeneous Interfaces

This work develops a unified framework for joint packet routing, link scheduling, and interface assignment in Het-MuNets with multiple concurrent flows that outperforms SP-BP operating on other baseline graph models and non-backpressure routing schemes in goodput, latency, and packet delivery rate.

Yujun Ming, Zhong-Yuan Zhao, F. Dagefu et al. · 0 citations