206 citations · 917 across the 24 of their papers we have counts for
26 papers
Zero- and Few-Shots Knowledge Graph Triplet Extraction with Large Language Models
Andrea Papaluca, Daniel Krefl, Sergio Mendez Rodriguez +2
In this work, we tested the Triplet Extraction (TE) capabilities of a variety of Large Language Models (LLMs) of different sizes in the Zero- and Few-Shots settings. In detail, we…
Product Jacobi-Theta Boltzmann machines with score matching
Andrea Pasquale, Daniel Krefl, Stefano Carrazza +1
The estimation of probability density functions is a non trivial task that over the last years has been tackled with machine learning techniques. Successful applications can be obt…
Modelling conditional probabilities with Riemann-Theta Boltzmann Machines
Stefano Carrazza, Daniel Krefl, Andrea Papaluca
The probability density function for the visible sector of a Riemann-Theta Boltzmann machine can be taken conditional on a subset of the visible units. We derive that the correspon…
Sampling the Riemann-Theta Boltzmann Machine
Stefano Carrazza, Daniel Krefl
We show that the visible sector probability density function of the Riemann-Theta Boltzmann machine corresponds to a gaussian mixture model consisting of an infinite number of comp…
Machine Learning of Calabi-Yau Volumes
Daniel Krefl, Rak-Kyeong Seong
We employ machine learning techniques to investigate the volume minimum of Sasaki-Einstein base manifolds of non-compact toric Calabi-Yau 3-folds. We find that the minimum volume c…
Non-Perturbative Quantum Geometry III
Daniel Krefl
The Nekrasov-Shatashvili limit of the refined topological string on toric Calabi-Yau manifolds and the resulting quantum geometry is studied from a non-perturbative perspective. Th…