ICML
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design
Download Abstract: Deep learning has achieved tremendous success in designing novel chemical compounds with desirable pharmaceutical properties. In this work, we focus on a new type of drug design problem — generating a small “linker” to physically attach two independent molecules with their distinct functions. The main computational challenges include: 1) the generation of linkers …
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How Powerful are Spectral Graph Neural Networks
Download Abstract: Spectral Graph Neural Network is a kind of Graph Neural Network (GNN) based on graph signal filters. Some models able to learn arbitrary spectral filters have emerged recently. However, few works analyze the expressive power of spectral GNNs. This paper studies spectral GNNs’ expressive power theoretically. We first prove that even spectral GNNs …
Latent Diffusion Energy-Based Model for Interpretable Text Modeling
Download Abstract: Latent space Energy-Based Models (EBMs), also known as energy-based priors, have drawn growing interests in generative modeling. Fueled by its flexibility in the formulation and strong modeling power of the latent space, recent works built upon it have made interesting attempts aiming at the interpretability of text modeling. However, latent space EBMs also …
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