Scalable Supervised Optimal Transport of Gaussian Mixture Models

Damin Kühn, Michael T Schaub

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Efficient Knowledge Transfer in Federated Bayesian Optimization through Neural Network Surrogates

Alexander Gräfe, Max van Gemmeren, Paul Brunzema, Sebastian Trimpe

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

Runtime Analysis of Cartesian Genetic Programming on MAX: A Proven Exponential Speedup

Duc-Cuong Dang, Roman Kalkreuth, Andre Opris

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Phase Transitions in Attention: A Bayesian Theory of Copy Head Emergence

Bayesian theory reveals softmax attention learns copy heads via a first-order data phase transition, unlike linear attention's second-order transition and crossover.

Itay Lavie, Kirsten Fischer, Andrey Lekov, Frederic Van Maele and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Dyna-Style Safety Augmented Reinforcement Learning: Staying Safe in the Face of Uncertainty

Dyna-SAuR learns scalable safety filters and policies via uncertainty-aware dynamics to reduce training failures by two orders of magnitude versus baselines.

Artur Eisele, Bernd Frauenknecht, Friedrich Solowjow, Sebastian Trimpe

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

Efficient Lookahead Encoding and Abstracted Width for Learning General Policies in Classical Planning

Holistic relational encoding and abstracted width enable GNN policies to learn general classical planning strategies efficiently, surpassing LAMA on IPC 2023 benchmarks.

Michael Aichmüller, Simon Ståhlberg, Martin Funkquist, Hector Geffner

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Brain-OF: An Omnifunctional Foundation Model for fMRI, EEG and MEG

Brain-OF is a multimodal foundation model jointly pretrained on fMRI, EEG, and MEG via unified sampling, sparse mixture-of-experts attention, and dual-domain masked modeling, achieving superior cross-modal neuroscience performance.

Hanning Guo, Hanwen Bi, Farah Abdellatif, Andrei Galbenus and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026