5 papers
Provably Reduced Sample Cost in Prior-Guided Hyperparameter Optimization
Leona Hennig, Jasmin Brandt, Lukas Fehring +3
Large-scale hyperparameter optimization (HPO) in automated machine learning (AutoML) consumes substantial computational resources, raising growing concerns about scalability and en…
Who Has The Final Say? Conformity Dynamics in ChatGPT's Selections
Clarissa Sabrina Arlinghaus, Tristan Kenneweg, Barbara Hammer +1
Large language models (LLMs) such as ChatGPT are increasingly integrated into high-stakes decision-making, yet little is known about their susceptibility to social influence. We co…
Uncertainty-Aware Remaining Lifespan Prediction from Images
Tristan Kenneweg, Philip Kenneweg, Barbara Hammer
Predicting mortality-related outcomes from images offers the prospect of accessible, noninvasive, and scalable health screening. We present a method that leverages pretrained visio…
JEPA for RL: Investigating Joint-Embedding Predictive Architectures for Reinforcement Learning
Tristan Kenneweg, Philip Kenneweg, Barbara Hammer
Joint-Embedding Predictive Architectures (JEPA) have recently become popular as promising architectures for self-supervised learning. Vision transformers have been trained using JE…
Generating Synthetic Genotypes using Diffusion Models
Philip Kenneweg, Raghuram Dandinasivara, Xiao Luo +2
In this paper, we introduce the first diffusion model designed to generate complete synthetic human genotypes, which, by standard protocols, one can straightforwardly expand into f…