Post #787

Graph ML News (Aug 12th) - ESM Disbandment, KDD’23, LoG’23 😮 The ESM team at Meta AI has been disbanded to a large surprise of the community - the suite of ESM protein language models (ESM-1, ESM-2) and ESMFold became very popular in the protein representation and generation, and things looked promising upon the release of the ESM Metagenomic Atlas with 600M+ protein structures. Some rumors say the team would continue working on the ESM stack at another place, so we’ll keep an eye on their next steps. KDD’23 has just finished in Long Beach - perhaps it is the most graph-packed data mining conference featuring 3 workshops and 10 tutorials on Graph ML topics. The proceedings are already available and full of graph papers. I attended the Graph Learning Benchmarks workshop last Sunday to participate in the panel discussion, met old and new friends, and enjoyed a less crowded venue than ICML (still socially drained after Hawaii though). The submission deadline for the best Graph ML conference Learning on Graph 2023 (LoG) is Aug 21st (AoE) and approaching — consider submitting if you didn’t like savage NeurIPS strong reject reviews 👺. For me, the LoG reviewing (both as an author and reviewer) and conference experience was the best in 2022, highly recommend! Weekend reading: AbDiffuser: Full-Atom Generation of In-Vitro Functioning Antibodies feat. Kyunghyun Cho and Andreas Loukas — a continuous (atom coordinates) and discrete (residue types) diffusion model for generating antibodies. “Laboratory experiments confirm that all 16 HER2 antibodies discovered were expressed at high levels and that 57.1% of selected designs were tight binders” 👀. Augmenting Recurrent Graph Neural Networks with a Cache feat. Nesreen Ahmed — introduces CacheGNNs with memory, sets a new SOTA (with a significant margin) on the Peptides-struct graph regression problem of the Long-Range Graph Benchmark. VQGraph: Graph Vector-Quantization for Bridging GNNs and MLPs feat. Jure Leskovec Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection feat. Stephan Günnemann