To Centralize or Not to Centralize: A Tale of Swarm Coordination. - Justin Hu; Ariana Bruno; Drew Zagieboylo; Mark Zhao; Brian Ritchken; Brendon Jackson; Joo Yeon Chae; Francois Mertil; Mateo Espinosa; Christina Delimitrou (CoRR, 2018)

An Open-Source Benchmark Suite for Microservices and Their Hardware-Software Implications for Cloud & Edge Systems. - Yu Gan 002; Yanqi Zhang; Dailun Cheng; Ankitha Shetty; Priyal Rathi; Nayan Katarki; Ariana Bruno; Justin Hu; Brian Ritchken; Brendon Jackson; Kelvin Hu; Meghna Pancholi; et al. (ASPLOS, 2019)

An Open-Source Benchmark Suite for Cloud and IoT Microservices. - Yu Gan 002; Yanqi Zhang; Dailun Cheng; Ankitha Shetty; Priyal Rathi; Nayan Katarki; Ariana Bruno; Justin Hu; Brian Ritchken; Brendon Jackson; Kelvin Hu; Meghna Pancholi; et al. (CoRR, 2019)

HiveMind: A Scalable and Serverless Coordination Control Platform for UAV Swarms. - Justin Hu; Ariana Bruno; Brian Ritchken; Brendon Jackson; Mateo Espinosa; Aditya Shah; Christina Delimitrou (CoRR, 2020)

Unveiling the Hardware and Software Implications of Microservices in Cloud and Edge Systems. - Yu Gan 002; Yanqi Zhang; Dailun Cheng; Ankitha Shetty; Priyal Rathi; Nayan Katarki; Ariana Bruno; Justin Hu; Brian Ritchken; Brendon Jackson; Kelvin Hu; Meghna Pancholi; et al. (IEEE Micro, 2020)

Efficient Decompositional Rule Extraction for Deep Neural Networks. - Mateo Espinosa Zarlenga; Zohreh Shams; Mateja Jamnik (CoRR, 2021)

Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off. - Mateo Espinosa Zarlenga; Pietro Barbiero; Gabriele Ciravegna; Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Zohreh Shams; Frédéric Precioso; Stefano Melacci; Adrian Weller; Pietro Lió; Mateja Jamnik (NeurIPS, 2022)

Concept Embedding Models. - Mateo Espinosa Zarlenga; Pietro Barbiero; Gabriele Ciravegna; Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Zohreh Shams; Frédéric Precioso; Stefano Melacci; Adrian Weller; Pietro Liò; Mateja Jamnik (CoRR, 2022)

Towards Robust Metrics for Concept Representation Evaluation. - Mateo Espinosa Zarlenga; Pietro Barbiero; Zohreh Shams; Dmitry Kazhdan; Umang Bhatt; Adrian Weller; Mateja Jamnik (AAAI, 2023)

Human Uncertainty in Concept-Based AI Systems. - Katherine Maeve Collins; Matthew Barker; Mateo Espinosa Zarlenga; Naveen Raman 001; Umang Bhatt; Mateja Jamnik; Ilia Sucholutsky; Adrian Weller; Krishnamurthy Dvijotham (AIES, 2023)

Interpretable Neural-Symbolic Concept Reasoning. - Pietro Barbiero; Gabriele Ciravegna; Francesco Giannini; Mateo Espinosa Zarlenga; Lucie Charlotte Magister; Alberto Tonda; Pietro Lio; Frédéric Precioso; Mateja Jamnik; Giuseppe Marra (ICML, 2023)

Learning to Receive Help: Intervention-Aware Concept Embedding Models. - Mateo Espinosa Zarlenga; Katie Collins; Krishnamurthy Dvijotham; Adrian Weller; Zohreh Shams; Mateja Jamnik (NeurIPS, 2023)

TabCBM: Concept-based Interpretable Neural Networks for Tabular Data. - Mateo Espinosa Zarlenga; Zohreh Shams; Michael E. Nelson; Been Kim; Mateja Jamnik (Trans. Mach. Learn. Res., 2023)

Efficient Bias Mitigation Without Privileged Information. - Mateo Espinosa Zarlenga; Swami Sankaranarayanan; Jerone T. A. Andrews; Zohreh Shams; Mateja Jamnik; Alice Xiang (ECCV (72), 2024)

From Must to May: Enabling Test-Time Feature Imputation and Interventions. - Evan Rex; Mateo Espinosa Zarlenga; Andrei Margeloiu; Mateja Jamnik (HI-AI@KDD, 2024)

Understanding Inter-Concept Relationships in Concept-Based Models. - Naveen Raman 001; Mateo Espinosa Zarlenga; Mateja Jamnik (ICML, 2024)

Workshop on Human-Interpretable AI. - Gabriele Ciravegna; Mateo Espinosa Zarlenga; Pietro Barbiero; Francesco Giannini; Zohreh Shams; Damien Garreau; Mateja Jamnik; Tania Cerquitelli (KDD, 2024)

Do Concept Bottleneck Models Obey Locality? - Naveen Raman 001; Mateo Espinosa Zarlenga; Juyeon Heo; Mateja Jamnik (CoRR, 2024)

Causal Concept Embedding Models: Beyond Causal Opacity in Deep Learning. - Gabriele Dominici; Pietro Barbiero; Mateo Espinosa Zarlenga; Alberto Termine; Martin Gjoreski; Giuseppe Marra; Marc Langheinrich (CoRR, 2024)

Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning. - Gabriele Dominici; Pietro Barbiero; Mateo Espinosa Zarlenga; Alberto Termine; Martin Gjoreski; Giuseppe Marra; Marc Langheinrich (ICLR, 2025)

Do Concept Bottleneck Models Respect Localities? - Naveen Janaki Raman; Mateo Espinosa Zarlenga; Juyeon Heo; Mateja Jamnik (Trans. Mach. Learn. Res., 2025)

Neural Interpretable Reasoning. - Pietro Barbiero; Giuseppe Marra; Gabriele Ciravegna; David Debot; Francesco De Santis; Michelangelo Diligenti; Mateo Espinosa Zarlenga; Francesco Giannini (CoRR, 2025)

Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts. - Andrea Pugnana; Riccardo Massidda; Francesco Giannini; Pietro Barbiero; Mateo Espinosa Zarlenga; Roberto Pellungrini; Gabriele Dominici; Fosca Giannotti; Davide Bacciu (CoRR, 2025)

Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts. - Mateo Espinosa Zarlenga; Gabriele Dominici; Pietro Barbiero; Zohreh Shams; Mateja Jamnik (CoRR, 2025)

Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization. - Emiliano Penaloza; Tianyue H. Zhan; Laurent Charlin; Mateo Espinosa Zarlenga (CoRR, 2025)

Foundations of Interpretable Models. - Pietro Barbiero; Mateo Espinosa Zarlenga; Alberto Termine; Mateja Jamnik; Giuseppe Marra (CoRR, 2025)