4.5k citations · 5.4k across the 27 of their papers we have counts for
31 papers
Quantification of Uncertainty with Adversarial Models in Medical Image Segmentation
Hana Jebril, Thomas Pinetz, Günter Klambauer +1
Reliable pixel-level uncertainty quantification holds the potential to transform clinical workflows by enabling high-fidelity longitudinal monitoring and distinguishing true pathol…
MolecularIQ: Characterizing Chemical Reasoning Capabilities Through Symbolic Verification on Molecular Graphs
Christoph Bartmann, Johannes Schimunek, Mykyta Ielanskyi +3
A molecule's properties are fundamentally determined by its composition and structure encoded in its molecular graph. Thus, reasoning about molecular properties requires the abilit…
Contrastive Geometric Learning Unlocks Unified Structure- and Ligand-Based Drug Design
Lisa Schneckenreiter, Sohvi Luukkonen, Lukas Friedrich +2
Structure-based and ligand-based computational drug design have traditionally relied on disjoint data sources and modeling assumptions, limiting their joint use at scale. In this w…
TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning
Andreas Auer, Patrick Podest, Daniel Klotz +3
In-context learning, the ability of large language models to perform tasks using only examples provided in the prompt, has recently been adapted for time series forecasting. This p…
xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference
Maximilian Beck, Korbinian Pöppel, Phillip Lippe +5
Recent breakthroughs in solving reasoning, math and coding problems with Large Language Models (LLMs) have been enabled by investing substantial computation budgets at inference ti…
LaM-SLidE: Latent Space Modeling of Spatial Dynamical Systems via Linked Entities
Florian Sestak, Artur Toshev, Andreas Fürst +3
Generative models are spearheading recent progress in deep learning, showcasing strong promise for trajectory sampling in dynamical systems as well. However, whereas latent space m…