Initializing LSTM internal states via manifold learning. - Felix P. Kemeth; Tom Bertalan; Nikolaos Evangelou; Tianqi Cui; Saurabh Malani; Ioannis G. Kevrekidis (CoRR, 2021)

Certified Invertibility in Neural Networks via Mixed-Integer Programming. - Tianqi Cui; Thomas Bertalan; George J. Pappas; Manfred Morari; Yannis G. Kevrekidis; Mahyar Fazlyab (L4DC, 2023)

Data-driven and Physics Informed Modelling of Chinese Hamster Ovary Cell Bioreactors. - Tianqi Cui; Tom S. Bertalan; Nelson Ndahiro; Pratik Khare; Michael Betenbaugh; Costas Maranas; Ioannis G. Kevrekidis (CoRR, 2023)

Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points. - Gianluca Fabiani; Nikolaos Evangelou; Tianqi Cui; Juan M. Bello-Rivas; Cristina P. Martin-Linares; Constantinos I. Siettos; Ioannis G. Kevrekidis (CoRR, 2023)

Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective Modeling. - Nikolaos Evangelou; Tianqi Cui; Juan M. Bello-Rivas; Alexei Makeev; Ioannis G. Kevrekidis (CoRR, 2023)

Some of the variables, some of the parameters, some of the times, with some physics known: Identification with partial information. - Saurabh Malani; Tom S. Bertalan; Tianqi Cui; Jose L. Avalos; Michael Betenbaugh; Ioannis G. Kevrekidis (Comput. Chem. Eng., 2023)

Data-driven and physics informed modeling of Chinese Hamster Ovary cell bioreactors. - Tianqi Cui; Tom Bertalan; Nelson Ndahiro; Pratik Khare; Michael Betenbaugh; Costas Maranas; Ioannis G. Kevrekidis (Comput. Chem. Eng., 2024)