Chemical Reactant Recommendation Using a Network of Organic Chemistry. - John Savage; Akihiro Kishimoto; Beat Buesser; Ernesto Diaz-Aviles; Carlos Alzate (RecSys, 2017)

AI Meets Chemistry. - Akihiro Kishimoto; Beat Buesser; Adi Botea (AAAI, 2018)

Learning Features For Relational Data. - Hoang Thanh Lam; Tran Ngoc Minh; Mathieu Sinn; Beat Buesser; Martin Wistuba (CoRR, 2018)

Recurrent Neural Networks for Autoregressive Moving Average Model Selection. - Bei Chen; Beat Buesser; Kelsey DiPietro (ICBK, 2019)

Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning. - Akihiro Kishimoto; Beat Buesser; Bei Chen; Adi Botea (NeurIPS, 2019)

How can AI Automate End-to-End Data Science? - Charu C. Aggarwal; Djallel Bouneffouf 001; Horst Samulowitz; Beat Buesser; Thanh Hoang; Udayan Khurana; Sijia Liu 001; Tejaswini Pedapati; Parikshit Ram; Ambrish Rawat; Martin Wistuba; Alexander G. Gray (CoRR, 2019)

Survey on Automated End-to-End Data Science? - Djallel Bouneffouf 001; Charu C. Aggarwal; Thanh Hoang; Udayan Khurana; Horst Samulowitz; Beat Buesser; Sijia Liu 001; Tejaswini Pedapati; Parikshit Ram; Ambrish Rawat; Martin Wistuba; Alexander G. Gray (IJCNN, 2020)

FAT: Federated Adversarial Training. - Giulio Zizzo; Ambrish Rawat; Mathieu Sinn; Beat Buesser (CoRR, 2020)

Automated Data Science for Relational Data. - Hoang Thanh Lam; Beat Buesser; Hong Min; Tran Ngoc Minh; Martin Wistuba; Udayan Khurana; Gregory Bramble; Theodoros Salonidis; Dakuo Wang; Horst Samulowitz (ICDE, 2021)

Automated Robustness with Adversarial Training as a Post-Processing Step. - Ambrish Rawat; Mathieu Sinn; Beat Buesser (CoRR, 2021)

Boundary Adversarial Examples Against Adversarial Overfitting. - Muhammad Zaid Hameed; Beat Buesser (CoRR, 2022)

Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMs. - Tomas Bueno Momcilovic; Dian Balta; Beat Buesser; Giulio Zizzo; Mark Purcell (ISSRE (Workshops), 2024)

Assuring Compliance of LLMs with EUAIA Robustness Demands. - Tomas Bueno Momcilovic; Beat Buesser; Giulio Zizzo; Mark Purcell; Dian Balta (Wirtschaftsinformatik, 2024)

Towards Assurance of LLM Adversarial Robustness using Ontology-Driven Argumentation. - Tomas Bueno Momcilovic; Beat Buesser; Giulio Zizzo; Mark Purcell; Dian Balta (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2024)

Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI. - Ambrish Rawat; Stefan Schoepf; Giulio Zizzo; Giandomenico Cornacchia; Muhammad Zaid Hameed; Kieran Fraser; Erik Miehling; Beat Buesser; Elizabeth M. Daly; Mark Purcell; Prasanna Sattigeri; Pin-Yu Chen; et al. (CoRR, 2024)

Towards Assuring EU AI Act Compliance and Adversarial Robustness of LLMs. - Tomas Bueno Momcilovic; Beat Buesser; Giulio Zizzo; Mark Purcell; Dian Balta (CoRR, 2024)

Knowledge-Augmented Reasoning for EUAIA Compliance and Adversarial Robustness of LLMs. - Tomas Bueno Momcilovic; Dian Balta; Beat Buesser; Giulio Zizzo; Mark Purcell (CoRR, 2024)

Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs. - Giulio Zizzo; Giandomenico Cornacchia; Kieran Fraser; Muhammad Zaid Hameed; Ambrish Rawat; Beat Buesser; Mark Purcell; Pin-Yu Chen; Prasanna Sattigeri; Kush R. Varshney (CoRR, 2025)

Design Patterns for Securing LLM Agents against Prompt Injections. - Luca Beurer-Kellner; Beat Buesser; Ana-Maria Cretu 001; Edoardo Debenedetti; Daniel Dobos; Daniel Fabian; Marc Fischer 002; David Froelicher; Kathrin Grosse; Daniel Naeff; Ezinwanne Ozoani; Andrew Paverd; et al. (CoRR, 2025)