Author

Mikkel Jordahn

2 papers indexed here

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#artificial intelligence Preprint Oct 2026

Atom-JEPA: Joint-Embedding Predictive Architecture for 3D Atomistic Systems

Atom-JEPA is introduced, a self-supervised pretraining framework that learns latent representations from unlabeled 3D structures through complementary atom-level and substructure-level objectives inspired by joint-embedding predictive architectures that achieves state-of-the-art performance on molecular ADMET and quant...

Kasper Helverskov Petersen, Rasmus Tirsgaard, François Cornet et al. · 1 citation

Jul 2026

Semi-Supervised Learning for Molecular Graphs via Ensemble Consensus

This work finds that training with an ensemble consensus objective increases robustness in models and exhibits an effect similar to knowledge distillation; an individual member of an ensemble trained this way outperforms a full ensemble trained in a traditional supervised fashion in almost all cases.

Rasmus Tirsgaard, Laurits Fredsgaard, Marisa Wodrich et al. · arXiv.org · 1 citation