17 citations · 25 across the 12 of their papers we have counts for
5 papers · 1 filter
Chemistry-Inspired Diffusion with Non-Differentiable Guidance
Yuchen Shen, Chenhao Zhang, Sijie Fu +3
Recent advances in diffusion models have shown remarkable potential in the conditional generation of novel molecules. These models can be guided in two ways: (i) explicitly, throug…
Reconstructing Galaxy Cluster Mass Maps using Score-based Generative Modeling
Alan Hsu, Matthew Ho, Joyce Lin +4
We present a novel approach to reconstruct gas and dark matter projected density maps of galaxy clusters using score-based generative modeling. Our diffusion model takes in mock SZ…
Recovering Time-Varying Networks From Single-Cell Data
Euxhen Hasanaj, Barnabás Póczos, Ziv Bar-Joseph
Gene regulation is a dynamic process that underlies all aspects of human development, disease response, and other key biological processes. The reconstruction of temporal gene regu…
GraphBPE: Molecular Graphs Meet Byte-Pair Encoding
Yuchen Shen, Barnabás Póczos
With the increasing attention to molecular machine learning, various innovations have been made in designing better models or proposing more comprehensive benchmarks. However, less…
Greener GRASS: Enhancing GNNs with Encoding, Rewiring, and Attention
Tongzhou Liao, Barnabás Póczos
Graph Neural Networks (GNNs) have become important tools for machine learning on graph-structured data. In this paper, we explore the synergistic combination of graph encoding, gra…