2 citations · 2 across the 25 of their papers we have counts for
4 papers · 1 filter
Beyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmark
Matthias Blaschke, Daniel Kienzle, Zsuzsanna Koczor-Benda +3
Generative molecular design is shaped by simple proxy benchmarks for drug-like properties and models pretrained on large pharmaceutical datasets. This combination yields strong ben…
Your Autoregressive Model Already Reveals the Causal Graph
Hugo Math, Rainer Lienhart
Autoregressive models trained via next-token prediction implicitly learn the conditional independence structure of their data-generating process. We exploit this observation to per…
One-Shot Multi-Label Causal Discovery in High-Dimensional Event Sequences
Hugo Math, Robin Schön, Rainer Lienhart
Understanding causality in event sequences with thousands of sparse event types is critical in domains such as healthcare, cybersecurity, or vehicle diagnostics, yet current method…
Towards Practical Multi-label Causal Discovery in High-Dimensional Event Sequences via One-Shot Graph Aggregation
Hugo Math, Rainer Lienhart
Understanding causality in event sequences where outcome labels such as diseases or system failures arise from preceding events like symptoms or error codes is critical. Yet remain…