Prov2ONE: An Algorithm for Automatically Constructing ProvONE Provenance Graphs. - Ajinkya Prabhune; Aaron Zweig; Rainer Stotzka; Michael Gertz 001; Jürgen Hesser (IPAW, 2016)

P-PIF: a ProvONE provenance interoperability framework for analyzing heterogeneous workflow specifications and provenance traces. - Ajinkya Prabhune; Aaron Zweig; Rainer Stotzka; Jürgen Hesser; Michael Gertz 001 (Distributed Parallel Databases, 2018)

Stochastic Optimization of Sorting Networks via Continuous Relaxations. - Aditya Grover; Eric Wang; Aaron Zweig; Stefano Ermon (ICLR (Poster), 2019)

Graphite: Iterative Generative Modeling of Graphs. - Aditya Grover; Aaron Zweig; Stefano Ermon (ICML, 2019)

Provably Efficient Third-Person Imitation from Offline Observation. - Aaron Zweig; Joan Bruna (UAI, 2020)

A Functional Perspective on Learning Symmetric Functions with Neural Networks. - Aaron Zweig; Joan Bruna (ICML, 2021)

Exponential Separations in Symmetric Neural Networks. - Aaron Zweig; Joan Bruna (NeurIPS, 2022)

Towards Antisymmetric Neural Ansatz Separation. - Aaron Zweig; Joan Bruna (CoRR, 2022)

On Single-Index Models beyond Gaussian Data. - Aaron Zweig; Loucas Pillaud-Vivien; Joan Bruna (NeurIPS, 2023)

Symmetric Single Index Learning. - Aaron Zweig; Joan Bruna (ICLR, 2024)

Theory of Symmetric Neural Networks - Aaron Zweig (2024)

Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations. - Zaikang Lin; Sei Chang; Aaron Zweig; Minseo Kang; Elham Azizi; David A. Knowles (CoRR, 2025)

Towards Identifiability of Interventional Stochastic Differential Equations. - Aaron Zweig; Zaikang Lin; Elham Azizi; David A. Knowles (CoRR, 2025)