Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization ...

Three recent studies by data-engineering specialist Swaminathan Sethuraman map out an efficiency agenda for the next ...

Graphs are among the most widely-used data structures in machine learning. Their power comes from the flexibility of capturing relations (edges) of collections of entities (nodes) which arise in a ...

Visual representation learning has made great ... information to complete specific tasks, including visual understanding (object detection, scene graph generation, visual grounding, visual ...