You can find below the assignment of groups to papers for the final poster.
Paper list
- F. Errica, D. Castellana, D. Bacciu, A. Micheli, The Infinite CGMM, ICML 2022 (PDF) - NOT ASSIGNED
- Causal normalizing flows: from theory to practice (PDF) - GROUP 3
- BISCUIT: Causal Representation Learning from Binary Interactions (PDF) - GROUP 10
- B. Chamberlain et al, Grand: Graph neural diffusion. ICML 2021 (PDF) - GROUP 11
- Gravina, M. Eliasof, C. Gallicchio, D. Bacciu, & C.-B. Schönlieb On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems. AAAI 2025 (PDF) - GROUP 6
- Dao Tri, Albert Gu, Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality, ICLR 2024 (PDF) - GROUP 4
- Y. Song & S. Ermon, Generative Modeling by Estimating Gradients of the Data Distribution, NeurIPS 2019 (PDF) - GROUP 9
- J. Austin, et al, Structured denoising diffusion models in discrete state-spaces, NeurIPS 2021 (PDF) - GROUP 2
- Clement Vignac et al, DiGress: Discrete Denoising diffusion for graph generation, ICLR 2023 (PDF) - GROUP 1
- Matteo Ninniri, Marco Podda, Davide Bacciu, Graph Diffusion that can Insert and Delete, NeurIPS 2025 (PDF) - GROUP 5
- Floor Eijkelboom et al, Variational Flow Matching for Graph Generation, NeurIPS 2024 (PDF) - GROUP 8
- Yiming Qin et al, DeFoG: Discrete Flow Matching for Graph Generation, ICML 2025 (PDF) - GROUP 12
- DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model. (PDF) - - GROUP 7