Neural Integral Equations. - Emanuele Zappala; Antonio Henrique de Oliveira Fonseca; Josue Ortega Caro; David van Dijk (CoRR, 2022)

AMPNet: Attention as Message Passing for Graph Neural Networks. - Syed Asad Rizvi; Nhi Nguyen; Haoran Lyu; Ben Christensen; Josue Ortega Caro; Emanuele Zappala; Maria Brbic; Rahul Madhav Dhodapkar; David van Dijk (CoRR, 2022)

Deep Neural Networks as the Semi-classical Limit of Topological Quantum Neural Networks: The problem of generalisation. - Antonino Marciano; Deen Chen 001; Filippo Fabrocini; Chris Fields 001; Matteo Lulli; Emanuele Zappala (CoRR, 2022)

Derivation problem for quandle algebras. - Mohamed Elhamdadi; Abdenacer Makhlouf; Sergei Silvestrov; Emanuele Zappala (Int. J. Algebra Comput., 2022)

Quantum Neural Networks and Topological Quantum Field Theories. - Antonino Marciano; Deen Chen 001; Filippo Fabrocini; Chris Fields 001; Enrico Greco; Niels Gresnigt; Krid Jinklub; Matteo Lulli; Kostas Terzidis; Emanuele Zappala (Neural Networks, 2022)

Neural Integro-Differential Equations. - Emanuele Zappala; Antonio Henrique de Oliveira Fonseca; Andrew Henry Moberly; Michael James Higley; Chadi Abdallah; Jessica A. Cardin; David van Dijk (AAAI, 2023)

Continuous Spatiotemporal Transformer. - Antonio Henrique de Oliveira Fonseca; Emanuele Zappala; Josue Ortega Caro; David van Dijk (ICML, 2023)

Continuous Spatiotemporal Transformers. - Antonio Henrique de Oliveira Fonseca; Emanuele Zappala; Josue Ortega Caro; David van Dijk (CoRR, 2023)

Operator Learning Meets Numerical Analysis: Improving Neural Networks through Iterative Methods. - Emanuele Zappala; Daniel LeVine; Sizhuang He; Syed Asad Rizvi; Sacha Levy; David van Dijk (CoRR, 2023)

Spectral methods for Neural Integral Equations. - Emanuele Zappala (CoRR, 2023)

BrainLM: A foundation model for brain activity recordings. - Josue Ortega Caro; Antonio Henrique de Oliveira Fonseca; Syed Asad Rizvi; Matteo Rosati; Christopher L. Averill; James L. Cross; Prateek Mittal; Emanuele Zappala; Rahul Madhav Dhodapkar; Chadi Abdallah; David van Dijk (ICLR, 2024)

Projection Methods for Operator Learning and Universal Approximation. - Emanuele Zappala (CoRR, 2024)

Universal Approximation of Operators with Transformers and Neural Integral Operators. - Emanuele Zappala; Maryam Bagherian (CoRR, 2024)

Leray-Schauder Mappings for Operator Learning. - Emanuele Zappala (CoRR, 2024)

CaLMFlow: Volterra Flow Matching using Causal Language Models. - Sizhuang He; Daniel LeVine; Ivan Vrkic; Marco Francesco Bressana; David Zhang; Syed Asad Rizvi; Yangtian Zhang; Emanuele Zappala; David van Dijk (CoRR, 2024)

Learning integral operators via neural integral equations. - Emanuele Zappala; Antonio Henrique de Oliveira Fonseca; Josue Ortega Caro; Andrew Henry Moberly; Michael James Higley; Jessica A. Cardin; David van Dijk (Nat. Mac. Intell., 2024)

Intelligence at the Edge of Chaos. - Shiyang Zhang; Aakash Patel; Syed Asad Rizvi; Nianchen Liu; Sizhuang He; Amin Karbasi; Emanuele Zappala; David van Dijk (ICLR, 2025)

Whether a quantum computation employs nonlocal resources is operationally undecidable. - Chris Fields 001; James F. Glazebrook; Antonino Marciano; Emanuele Zappala (CoRR, 2025)

Non-Markovian Discrete Diffusion with Causal Language Models. - Yangtian Zhang; Sizhuang He; Daniel LeVine; Lawrence Zhao; David Zhang; Syed Asad Rizvi; Emanuele Zappala; Rex Ying; David van Dijk (CoRR, 2025)

Neural Integral Operators for Inverse problems in Spectroscopy. - Emanuele Zappala; Alice Giola; Andreas Kramer; Enrico Greco (CoRR, 2025)