Zonotope hit-and-run for efficient sampling from projection DPPs

1 code implementation • ICML 2017 • Guillaume Gautier, Rémi Bardenet, Michal Valko

Previous theoretical results yield a fast mixing time of our chain when targeting a distribution that is close to a projection DPP, but not a DPP in general.

Point Processes Recommendation Systems

DPPy: Sampling DPPs with Python

2 code implementations • 19 Sep 2018 • Guillaume Gautier, Guillermo Polito, Rémi Bardenet, Michal Valko

Determinantal point processes (DPPs) are specific probability distributions over clouds of points that are used as models and computational tools across physics, probability, statistics, and more recently machine learning.

BIG-bench Machine Learning Point Processes

On two ways to use determinantal point processes for Monte Carlo integration

1 code implementation • NeurIPS 2019 • Guillaume Gautier, Rémi Bardenet, Michal Valko

In the absence of DPP machinery to derive an efficient sampler and analyze their estimator, the idea of Monte Carlo integration with DPPs was stored in the cellar of numerical integration.

Numerical Integration Point Processes

OpenVVC: a Lightweight Software Decoder for the Versatile Video Coding Standard

1 code implementation • 24 May 2022 • Thomas Amestoy, Pierre-loup Cabarat, Guillaume Gautier, Wassim Hamidouche, Daniel Menard

The new generation video coding standard, called Versatile Video Coding (VVC), has been developed by the Joint Video Experts Team, and offers coding capability beyond the previous generation High Efficiency Video Coding (HEVC) standard.

Performance Analysis of Optimized Versatile Video Coding Software Decoders on Embedded Platforms

no code implementations • 30 Jun 2022 • Anup Saha, Wassim Hamidouche, Miguel Chavarrías, Guillaume Gautier, Fernando Pescador, Ibrahim Farhat

Hence, in July 2020 the Versatile Video Coding (VVC) standard was released providing up to 50% bit-rate saving for the same video quality compared to its predecessor High Efficiency Video Coding (HEVC).