Post #831

GraphML News (March 16th) - RelationRx round, Caduceus, Blogposts, WholeGraph 💸 Relation Therapeutics, the drug discovery company, raises $35M seed funding led by DCVC and NVentures (VC arm of NVIDIA) - making it $60M in total after factoring in the previous round in 2022. Relation is developing treatments for osteoporosis and other bone-related diseases. ⚕️The race between Mamba and Hyena-like architectures for long-context DNA modeling is heating up: Caduceus by Yair Schiff featuring Tri Dao and Albert Gu is the first bi-directional Mamba equivariant to the reverse complement (RC) symmetry of DNA. Similarly to the recent Evo, it supports sequence lengths up to 131k. In turn, a new blog post by Hazy Research on Evo hinted upon the new Mechanistic Architecture Design framework that employs synthetic probes to check long-range modeling capabilities. 💬 A new Medium blogpost by Xiaoxin He (NUS Singapore) on chatting with your graph - dedicated to the recent G-Retriever paper on graph-based RAG for question answering tasks. The post goes through the technical details (perhaps the most interesting part is prize-collecting Steiner Tree for subgraph retrieval) and positions the work in the flurry of recent Graph + LLM approaches including Talk Like a Graph (highlighted in the recent Google Research blogpost) and Let the Graph do the Talking. Fun fact: now we have 2 different datasets named GraphQA with completely different contents and tasks (one from G-Retriever, another one from the Google papers). 💽 The WholeGraph Storage by NVIDIA for PyG and DGL - a handy way for distributed setups to keep a single graph in the shared storage accessible by the workers. WholeGraph comes in three flavors: continuous, chunked, and distributed. Weekend reading: Personalized Audiobook Recommendations at Spotify Through Graph Neural Networks by Marco De Nadai, Francesco Fabbri, and the Spotify team - Heterogeneous GNNs + The Two (MLP) Towers for SOTA RecSys. Universal Representation of Permutation-Invariant Functions on Vectors and Tensors by Puoya Tabaghi and Yusu Wang (UCSD) - when encoding sets of N elements of D-dimensional vectors, DeepSets require a latent dimension of N^D. This cool work reduces this bound to 2ND 👀. Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields by Yi-Lun Liao, Tess Smidt, Abhishek Das - the success of a Noisy Nodes-like auxiliary denoising objective is extended to non-equilibrium structures thanks to encoding forces of non-equilibrium structures. Yields SOTA on OpenCatalyst (if you have 16-128 V100’s though).