116 citations · 478 across the 22 of their papers we have counts for
3 papers · 2 filters
Addressing caveats of neural persistence with deep graph persistence
Leander Girrbach, Anders Christensen, Ole Winther +2
Neural Persistence is a prominent measure for quantifying neural network complexity, proposed in the emerging field of topological data analysis in deep learning. In this work, how…
Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation
Giorgio Giannone, Akash Srivastava, Ole Winther +1
Generative models have had a profound impact on vision and language, paving the way for a new era of multimodal generative applications. While these successes have inspired researc…
Unifying Molecular and Textual Representations via Multi-task Language Modelling
Dimitrios Christofidellis, Giorgio Giannone, Jannis Born +3
The recent advances in neural language models have also been successfully applied to the field of chemistry, offering generative solutions for classical problems in molecular desig…