InfoQ

Inside Target’s LLM-Based System for Semantic Matching in Marketing Forecast Pipelines

Target built a generative AI system to improve marketing campaign forecasting by retrieving and ranking similar historical ...
PNAS

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in nonequilibrium systems

Multiscale systems far from equilibrium are challenging to model due to coupling between unresolved physics and emergent stochastic behavior. Our hybrid machine learning framework generates models ...
InfoQ

Meta Details GEM Ads Model Using LLM-Scale Training, Hybrid Parallelism, and Knowledge Transfer

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Erik Steiger discusses the operational pain ...
GitHub

Identifying compound-protein interactions with knowledge graph embedding of perturbation transcriptomics

This repo contains a PyTorch implementation for PertKGE, which is model proposed in our paper "Identifying compound-protein interactions with knowledge graph embedding of perturbation transcriptomics" ...
C&EN

Molecular Graph Generation by Decomposition and Reassembling

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Designing molecular structures with desired chemical properties is an essential task ...
GitHub

TorchKGE: Knowledge Graph embedding in Python and Pytorch.

If you find this code useful in your research, please consider citing our paper (presented at IWKG-KDD 2020): @inproceedings{arm2020torchkge, title={TorchKGE: Knowledge Graph Embedding in Python and ...