Alex Tseng — accepted AI-conference papers

2023

Improving Graph Generation by Restricting Graph Bandwidth

Nathaniel Lee Diamant, Alex Tseng, Kangway V Chuang, Tommaso Biancalani, Gabriele Scalia

ICML 2023poster

Deep graph generative modeling has proven capable of learning the distribution of complex, multi-scale structures characterizing real-world graphs. However, one of the main limitations of existing methods is their large output space, which limits generation scalability and hinders accurate modeling…

Cited by 11 Source ↗PDF ↗code ↗Scholar ↗

2020

Fourier-transform-based attribution priors improve the interpretability and stability of deep learning models for genomics

Alex Tseng, Avanti Shrikumar, Anshul Kundaje

NeurIPS 2020poster

Deep learning models can accurately map genomic DNA sequences to associated functional molecular readouts such as protein-DNA binding data. Base-resolution importance (i.e. "attribution") scores inferred from these models can highlight predictive sequence motifs and syntax. Unfortunately, these mode…

Cited by 39 Source ↗PDF ↗Scholar ↗