56 citations · 150 across the 7 of their papers we have counts for
7 papers
Sublinear Variational Optimization of Gaussian Mixture Models with Millions to Billions of Parameters
Sebastian Salwig, Till Kahlke, Florian Hirschberger +2
Gaussian Mixture Models (GMMs) range among the most frequently used models in machine learning. However, training large, general GMMs becomes computationally prohibitive for data s…
Adiabatic demagnetization refrigeration to mK temperatures with the distorted square lattice magnet NaYbGeO
U. Arjun, K. M. Ranjith, A. Jesche +3
We report the synthesis, characterization, low-temperature magnetic, and thermodynamic measurements of the novel milli-Kelvin adiabatic demagnetization refrigeration (mK-ADR) candi…
Efficient adiabatic demagnetization refrigeration to below 50 mK with UHV compatible Ytterbium diphosphates YbPO (Na, K)
U. Arjun, K. M. Ranjith, A. Jesche +3
Attaining milli-Kelvin temperatures is often a prerequisite for the study of novel quantum phenomena and the operation of quantum devices. Adiabatic demagnetization refrigeration (…
Adiabatic demagnetization cooling well below the magnetic ordering temperature in the triangular antiferromagnet KBaGd(BO3)2
A. Jesche, N. Winterhalter-Stocker, F. Hirschberger +5
Crystal structure, thermodynamic properties, and adiabatic demagnetization refrigeration (ADR) effect in the spin-7/2 triangular antiferromagnet KBaGd(BO3)2 are reported. With the…
LiSr[MnN]: a magnetically ordered, metallic nitride
F. Hirschberger, T. J. Ballé, C. Haas +5
LiSr[MnN] single crystals were successfully grown out of Li rich flux. The crystal structure was determined by single crystal X-ray diffraction and revealed almost linear $…
Generic Unsupervised Optimization for a Latent Variable Model With Exponential Family Observables
Hamid Mousavi, Jakob Drefs, Florian Hirschberger +1
Latent variable models (LVMs) represent observed variables by parameterized functions of latent variables. Prominent examples of LVMs for unsupervised learning are probabilistic PC…
Large Scale Clustering with Variational EM for Gaussian Mixture Models
Florian Hirschberger, Dennis Forster, Jörg Lücke
This paper represents a preliminary (pre-reviewing) version of a sublinear variational algorithm for isotropic Gaussian mixture models (GMMs). Further developments of the algorithm…