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
Max Schattauer will present at the Prompt Engineering Conference 2024, discussing how query contextualization and prompt engineering with TextGrad improve chatbot retrieval accuracy, ensuring high-quality, industry-grade solutions and enhanced customer satisfaction.
Event
Perelyn's Chief AI Scientist will be presenting at Neo4j Nodes 2024 on how hierarchical graph structures improve AI retrieval precision underpin applications such as Adiu Health's automated documentation of medical consultations.
