Official implementation of "FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching" (ICLR 2026)
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Apr 24, 2026 - Python
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graph-generative-models
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Official code for "Flatten Graphs as Sequences: Transformers are scalable graph generators" (NeurIPS 2025)
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Oct 17, 2025 - Python
Scalable and privacy-enhanced graph generative models for benchmark graph neural networks
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Nov 1, 2023 - Python
Benchmarking suite for evaluating the performance of graph processing on synthetic graph data
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Jun 13, 2026 - Jupyter Notebook
This is the official implementation of the FLAGG framework as published in the 2026 JMLR paper "FLAGG: Flexible Autoregressive Graph Generation". The framework is highly customizable to create new combinations of autoregressive graph generative models with existing and yet-to-exist one-shot models.
graph-generation graph-generative-model graph-generative-models autoregressive-generation autoregressive-generative-model autoregressive-generative-models
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Apr 30, 2026 - Jupyter Notebook
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