8 citations · 15 across the 5 of their papers we have counts for
5 papers
Pyramid Vector Quantization for LLMs
Tycho F. A. van der Ouderaa, Maximilian L. Croci, Agrin Hilmkil +1
Recent works on compression of large language models (LLM) using quantization considered reparameterizing the architecture such that weights are distributed on the sphere. This dem…
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci +6
We introduce QuaRot, a new Quantization scheme based on Rotations, which is able to quantize LLMs end-to-end, including all weights, activations, and KV cache in 4 bits. QuaRot rot…
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari do Nascimento +2
Large language models have become the cornerstone of natural language processing, but their use comes with substantial costs in terms of compute and memory resources. Sparsificatio…
Online parameter inference for the simulation of a Bunsen flame using heteroscedastic Bayesian neural network ensembles
Maximilian L. Croci, Ushnish Sengupta, Matthew P. Juniper
This paper proposes a Bayesian data-driven machine learning method for the online inference of the parameters of a G-equation model of a ducted, premixed flame. Heteroscedastic Bay…
Real-time parameter inference in reduced-order flame models with heteroscedastic Bayesian neural network ensembles
Ushnish Sengupta, Maximilian L. Croci, Matthew P. Juniper
The estimation of model parameters with uncertainties from observed data is a ubiquitous inverse problem in science and engineering. In this paper, we suggest an inexpensive and ea…