GraphML News (July 1st)

⚛️ 3rd Open Catalyst challenge has been announced! This year the task is to predict the global minimum binding energy (adsorption energy) given an adsorbate and catalyst surface. The main dataset includes the new OC20-Dense split with roughly 15K initial structures and 3M frames. Baselines are GemNet-OC and Equivariant Spheric Channel Network (eSCN). Results will be announced at NeurIPS’23.

🎙️ The biennial Sampling Theory and Applications Conference (SAMPTA) 2023 will soon take place at Yale in July 10-14. This year will feature invited talks by Soledad Villar, Gitta Kutyniok, Michael Bronstein, Dan Spielman, and other prominent researchers. Registrations are still open!

🧬 Folks in comp bio might want to refresh the background on state space models (SSMs) - HyenaDNA, a collab between Stanford, Harvard, and Mila, is a DNA model with a whopping context length of up to 1M tokens of single nucleotides. HyenaDNA scales to lengths unattainable even by linear Transformers and shows SOTA of 23 genomic tasks. Pre-trained checkpoints are already on HuggingFace. The authors hint upon further generative applications, so we’ll keep an eye on that.

A few words about hypergraphs: the anonymous author put on a tutorial on the basics of hypergraphs and building hypergraph GNNs. And a new work Hypergraph factorisation for multi-tissue gene expression imputation shows how to use message passing hypergraph NNs for processing gene expression in comp bio applications.