Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies. - T. Konstantin Rusch; Siddhartha Mishra (ICLR, 2021)

UnICORNN: A recurrent model for learning very long time dependencies. - T. Konstantin Rusch; Siddhartha Mishra (ICML, 2021)

Enhancing Accuracy of Deep Learning Algorithms by Training with Low-Discrepancy Sequences. - Siddhartha Mishra; T. Konstantin Rusch (SIAM J. Numer. Anal., 2021)

Higher-Order Quasi-Monte Carlo Training of Deep Neural Networks. - Marcello Longo; Siddhartha Mishra; T. Konstantin Rusch; Christoph Schwab (SIAM J. Sci. Comput., 2021)

Long Expressive Memory for Sequence Modeling. - T. Konstantin Rusch; Siddhartha Mishra; N. Benjamin Erichson; Michael W. Mahoney (ICLR, 2022)

Graph-Coupled Oscillator Networks. - T. Konstantin Rusch; Ben Chamberlain 001; James Rowbottom; Siddhartha Mishra; Michael M. Bronstein (ICML, 2022)

Gradient Gating for Deep Multi-Rate Learning on Graphs. - T. Konstantin Rusch; Benjamin Paul Chamberlain; Michael W. Mahoney; Michael M. Bronstein; Siddhartha Mishra (ICLR, 2023)

Neural Oscillators are Universal. - Samuel Lanthaler; T. Konstantin Rusch; Siddhartha Mishra (NeurIPS, 2023)

Multi-Scale Message Passing Neural PDE Solvers. - Léonard Equer; T. Konstantin Rusch; Siddhartha Mishra (CoRR, 2023)

A Survey on Oversmoothing in Graph Neural Networks. - T. Konstantin Rusch; Michael M. Bronstein; Siddhartha Mishra (CoRR, 2023)

Message-Passing Monte Carlo: Generating low-discrepancy point sets via Graph Neural Networks. - T. Konstantin Rusch; Nathan Kirk; Michael M. Bronstein; Christiane Lemieux; Daniela Rus (CoRR, 2024)

Improving Efficiency of Sampling-based Motion Planning via Message-Passing Monte Carlo. - Makram Chahine; T. Konstantin Rusch; Zach J. Patterson; Daniela Rus (CoRR, 2024)

Relaxed Equivariance via Multitask Learning. - Ahmed A. A. Elhag; T. Konstantin Rusch; Francesco Di Giovanni; Michael M. Bronstein (CoRR, 2024)

How does over-squashing affect the power of GNNs? - Francesco Di Giovanni; T. Konstantin Rusch; Michael M. Bronstein; Andreea Deac; Marc Lackenby; Siddhartha Mishra; Petar Velickovic (Trans. Mach. Learn. Res., 2024)

Oscillatory State-Space Models. - T. Konstantin Rusch; Daniela Rus (ICLR, 2025)

Low Stein Discrepancy via Message-Passing Monte Carlo. - Nathan Kirk; T. Konstantin Rusch; Jakob Zech; Daniela Rus (CoRR, 2025)

Learning to Dissipate Energy in Oscillatory State-Space Models. - Jared Boyer; T. Konstantin Rusch; Daniela Rus (CoRR, 2025)

Learning to Move in Rhythm: Task-Conditioned Motion Policies with Orbital Stability Guarantees. - Maximilian Stölzle; T. Konstantin Rusch; Zach J. Patterson; Rodrigo Pérez-Dattari; Francesco Stella; Josie Hughes; Cosimo Della Santina; Daniela Rus (CoRR, 2025)