Neural representation-learning for generative modeling in biology
Smita Krishnaswamy

Introduction
Timo Dickscheid & Stefan Kesselheim

Welcome Note
Ina Brandes, Minister for Culture and Science, NRW

Most efficient AI training at scale on JUPITER
Thomas Lippert

Open foundation models: reproducible science of transferable learning
Jenia Jitsev

Decoding Human Brain Architecture with AI
Christian Schiffer

GPUs and Machine Learning for Optimization
Paul Swoboda

WestAI – Service Center for Artificial Intelligence
Joachim Köhler

Masks, Signs, and Learning Rate Rewinding
Advait Gadhikar

MemSpikingTM: Neuromorphic sequence learning with memristive in-memory computing – from algorithm to hardware demonstration
Sebastian Siegel

Towards Energy-Efficient Satellite-Onboard Landcover Classification with Spiking Neural Networks
Conrad Albrecht

DataDream: Few-shot Guided Dataset Generation
Jae Myung Kim

SimulationBasedInference.jl: A flexible toolkit for Bayesian inference with process-based models
Brian Groenke

Foundation models: Reporting electricity consumption is essential for sustainable AI
Marie Piraud

HPC Directions in AI Applications for Earth System Science
Stan Posey

Helmholtz Blablador: An Inference Server for Scientific Large Language Models
Alexandre Strube

COMPASS: Enhancing Deep Learning Based Molecular Docking Insights for Comprehensive Analysis
Ahmet Sarigun

Enhancing clinical immunology through global Swarm Learning: A pioneering approach for ML-based clinical diagnostics
Stefanie Warnat-Herresthal

Deep Learning Improved Seasonal Forecasts for the Blue Nile Basin
Rebecca Wiegels

FastGPR: divide-and-conquer technique in neuroimaging data shortens training time and improves accuracy
Federico Raimondo

Generative Lung Architecture Modeling (GLAM)
Ella Bahry

Delineating the Effective Use of Self-Supervised Learning in Single-Cell Genomics
Till Richter

Enhancing Gene Expression Representation Learning for Improved Drug Response Prediction through Data Augmentation
Diyuan Lu

Application and Evaluation of Generative Adversarial Networks to Electroencephalography Data
Farah Abdellatif

Topological Point Cloud Clustering: Relating local features and global topology of networks and point clouds.
Vincent Grande

Multi-Source Auxiliary Tasks supported Monocular Depth Estimation
Alessio Quercia

Ensemble-based Density Estimation with Randomized Moment Matching in Neural Networks
Tobias Schanz

Why so negative? A General Approach for Neural Quasiprobabilistic Likelihood Ratio Estimation with Negatively Weighted Data
Stephen Jiggins

Multi-output Gaussian Processes for Integration of Multi Omics Data
Zahra Moslehi

Deep Differentiable Emulators for NEMO simulations
Vien MInh Nguyen-Thanh