Self-Tuning Hamiltonian Monte Carlo for Accelerated Sampling. - Henrik Christiansen; Federico Errica; Francesco Alesiani (CoRR, 2023)

Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching. - Federico Errica; Henrik Christiansen; Viktor Zaverkin; Takashi Maruyama; Mathias Niepert; Francesco Alesiani (CoRR, 2023)

Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing. - Viktor Zaverkin; Francesco Alesiani; Takashi Maruyama; Federico Errica; Henrik Christiansen; Makoto Takamoto; Nicolas Weber; Mathias Niepert (NeurIPS, 2024)

Adaptive Width Neural Networks. - Federico Errica; Henrik Christiansen; Viktor Zaverkin; Mathias Niepert; Francesco Alesiani (CoRR, 2025)

Geometric Kolmogorov-Arnold Superposition Theorem. - Francesco Alesiani; Takashi Maruyama; Henrik Christiansen; Viktor Zaverkin (CoRR, 2025)

Fast, Modular, and Differentiable Framework for Machine Learning-Enhanced Molecular Simulations. - Henrik Christiansen; Takashi Maruyama; Federico Errica; Viktor Zaverkin; Makoto Takamoto; Francesco Alesiani (CoRR, 2025)

Variational Kolmogorov-Arnold Network. - Francesco Alesiani; Henrik Christiansen; Federico Errica (CoRR, 2025)