Publications

Preprints / Under Review

1. Pedram Bakhtiarifard, Tong Chen, Jonathan Wenshøj, Erik B. Dam, Raghavendra Selvan: Algorithmic Simplification of Neural Networks with Mosaic-of-Motifs, preprint, 2026. [link]

2. Jonathan Wenshøj, Tong Chen, Bob Pepin, Raghavendra Selvan: CoDeQ: End-to-End Joint Model Compression with Dead-Zone Quantizer for High-Sparsity and Low-Precision Networks, preprint, 2025. [link]

Peer-Reviewed Conference Papers

1. Hallgrimur Thorsteinsson, Valdemar J. Henriksen, Daniel I.R. Cruz, Raghavendra Selvan, Tong Chen: An Empirical Study of the Influence of Adversarial Fine-Tuning on Compressed Neural Networks, published in Scandinavian Conference on AI (SCAI), 2026. [link, code]

2. Tong Chen, Raghavendra Selvan: Is Adversarial Training with Compressed Datasets Effective? published in Scandinavian Conference on Image Analysis (SCIA), 2025. [link, code]

3. Tong Chen, Jean-Bernard Lasserre, Victor Magron, Edouard Pauwels: Semialgebraic representation of monotone deep equilibrium models and applications to certification, published in NeurIPS, 2021. [bib, link, code]

4. Tong Chen, Jean-Bernard Lasserre, Victor Magron, Edouard Pauwels: Semialgebraic Optimization for Lipschitz Constants of ReLU Networks, published in NeurIPS, 2020. [bib, link, code]

Journal Articles

1. Tong Chen, Raghavendra Selvan: A Discrepancy-Based Perspective on Dataset Condensation, published in TMLR, 2026. [link]

2. Tong Chen, Jean-Bernard Lasserre, Victor Magron, Edouard Pauwels: A Sublevel Moment-SOS Hierarchy for Polynomial Optimization, published in Computational Optimization and Applications, 2022. [bib, link, code]