On Thursday, @oovcharenko.bsky.social will present her research on "scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data". This paper is joint work with ETH Zuerich and was selected as a spotlight poster:

icml.cc/virtual/2025...

(2/3)

This work is done at BIFOLD @xtraexer.bsky.social in collaboration with @matthiasboehm7.bsky.social.

MEMPHIS extends LIMA's lineage-based reuse to Spark and GPU. MEMPHIS offers a unified cache abstraction with multi-backend data objects, enabling reuse of Spark RDDs and GPU pointers, and a robust integration with Apache SystemDS compiler and runtime.