4 citations · 7 across the 8 of their papers we have counts for
3 papers · 1 filter
Optimal Embedding Guided Negative Sample Generation for Knowledge Graph Link Prediction
Makoto Takamoto, Daniel Oñoro-Rubio, Wiem Ben Rim +2
Knowledge graph embedding (KGE) models encode the structural information of knowledge graphs to predicting new links. Effective training of these models requires distinguishing bet…
Fast, Modular, and Differentiable Framework for Machine Learning-Enhanced Molecular Simulations
Henrik Christiansen, Takashi Maruyama, Federico Errica +3
We present an end-to-end differentiable molecular simulation framework (DIMOS) for molecular dynamics and Monte Carlo simulations. DIMOS easily integrates machine-learning-based in…
Geometric Kolmogorov-Arnold Superposition Theorem
Francesco Alesiani, Takashi Maruyama, Henrik Christiansen +1
The Kolmogorov-Arnold Theorem (KAT), or more generally, the Kolmogorov Superposition Theorem (KST), establishes that any non-linear multivariate function can be exactly represented…