News
We are thrilled to announce that our contribution to this year’s ICML Topological Deep Learning Challenge secured both 2nd and 3rd place in the competition’s respective categories!
Topological Deep Learning enhances neural network performance by leveraging topological structures in data. Our approach centered around a hypergraph-based solution to optimize information flow in large-scale networks. Hypergraphs have proven effective in diverse applications, including medical knowledge graph optimization, logistics, and business process enhancement.
The 2024 Topological Deep Learning Challenge was jointly organized by TAG-DS and PyT-Team and hosted by the Geometry-grounded Representation Learning and Generative Modeling (GRaM) Workshop at ICML 2024.
We’re proud of our team’s success and look forward to continuing to innovate in the field of topological deep learning.
More information about the challenge and its outcomes can be found here.
Event
Our colleagues showcased how Adiu Health uses GraphRAG and Neo4j to enhance clinical workflows with LLMs during a live Neo4j session. Watch the full talk.
Event
Perelyn will attend DMEA 2025 in Berlin to connect with healthcare leaders and explore AI solutions that drive innovation, compliance, and efficiency across the digital health ecosystem.
