Quantitative Assessment of Robotic Swarm Coverage. - Brendon G. Anderson; Eva Loeser; Marissa Gee; Fei Ren; Swagata Biswas; Olga Turanova; Matt Haberland; Andrea L. Bertozzi (ICINCO (2), 2018)

Quantifying Robotic Swarm Coverage. - Brendon G. Anderson; Eva Loeser; Marissa Gee; Fei Ren; Swagata Biswas; Olga Turanova; Matt Haberland; Andrea L. Bertozzi (ICINCO (Selected Papers), 2018)

Global Optimality Guarantees for Nonconvex Unsupervised Video Segmentation. - Brendon G. Anderson; Somayeh Sojoudi (Allerton, 2019)

Tightened Convex Relaxations for Neural Network Robustness Certification. - Brendon G. Anderson; Ziye Ma; Jingqi Li 001; Somayeh Sojoudi (CDC, 2020)

Data-Driven Assessment of Deep Neural Networks with Random Input Uncertainty. - Brendon G. Anderson; Somayeh Sojoudi (CoRR, 2020)

Partition-Based Convex Relaxations for Certifying the Robustness of ReLU Neural Networks. - Brendon G. Anderson; Ziye Ma; Jingqi Li 001; Somayeh Sojoudi (CoRR, 2021)

Node-Variant Graph Filters in Graph Neural Networks. - Fernando Gama; Brendon G. Anderson; Somayeh Sojoudi (CoRR, 2021)

A Sequential Greedy Approach for Training Implicit Deep Models. - Tanmay Gautam; Brendon G. Anderson; Somayeh Sojoudi; Laurent El Ghaoui (CDC, 2022)

Certified Robustness via Locally Biased Randomized Smoothing. - Brendon G. Anderson; Somayeh Sojoudi (L4DC, 2022)

An Overview and Prospective Outlook on Robust Training and Certification of Machine Learning Models. - Brendon G. Anderson; Tanmay Gautam; Somayeh Sojoudi (CoRR, 2022)

Tight Certified Robustness via Min-Max Representations of ReLU Neural Networks. - Brendon G. Anderson; Samuel Pfrommer; Somayeh Sojoudi (CDC, 2023)

Asymmetric Certified Robustness via Feature-Convex Neural Networks. - Samuel Pfrommer; Brendon G. Anderson; Julien Piet; Somayeh Sojoudi (NeurIPS, 2023)

Evolutionary Games on Infinite Strategy Sets: Convergence to Nash Equilibria via Dissipativity. - Brendon G. Anderson; Somayeh Sojoudi; Murat Arcak (CoRR, 2023)

Projected Randomized Smoothing for Certified Adversarial Robustness. - Samuel Pfrommer; Brendon G. Anderson; Somayeh Sojoudi (Trans. Mach. Learn. Res., 2023)

Data-Driven Certification of Neural Networks With Random Input Noise. - Brendon G. Anderson; Somayeh Sojoudi (IEEE Trans. Control. Netw. Syst., 2023)

Approximately Gaussian Replicator Flows: Nonconvex Optimization as a Nash-Convergent Evolutionary Game. - Brendon G. Anderson; Samuel Pfrommer; Somayeh Sojoudi (CDC, 2024)

Transport of Algebraic Structure to Latent Embeddings. - Samuel Pfrommer; Brendon G. Anderson; Somayeh Sojoudi (ICML, 2024)

Mixing classifiers to alleviate the accuracy-robustness trade-off. - Yatong Bai; Brendon G. Anderson; Somayeh Sojoudi (L4DC, 2024)

Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing. - Yatong Bai; Brendon G. Anderson; Aerin Kim; Somayeh Sojoudi (SIAM J. Math. Data Sci., 2024)

Provably Robust Machine Learning through Structure-Aware Computation - Brendon G. Anderson (2024)