HyperShot: Few-Shot Learning by Kernel HyperNetworks

1 code implementation • 21 Mar 2022 • Marcin Sendera, Marcin Przewięźlikowski, Konrad Karanowski, Maciej Zięba, Jacek Tabor, Przemysław Spurek

Few-shot models aim at making predictions using a minimal number of labeled examples from a given task.

Few-Shot Image Classification Few-Shot Learning

Non-Gaussian Gaussian Processes for Few-Shot Regression

1 code implementation • NeurIPS 2021 • Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Tomasz Trzciński, Przemysław Spurek, Maciej Zięba

This makes the GP posterior locally non-Gaussian, therefore we name our method Non-Gaussian Gaussian Processes (NGGPs).

Few-Shot Learning Gaussian Processes +2

Flow-based SVDD for anomaly detection

no code implementations • 10 Aug 2021 • Marcin Sendera, Marek Śmieja, Łukasz Maziarka, Łukasz Struski, Przemysław Spurek, Jacek Tabor

We propose FlowSVDD -- a flow-based one-class classifier for anomaly/outliers detection that realizes a well-known SVDD principle using deep learning tools.

Anomaly Detection One-class classifier

OneFlow: One-class flow for anomaly detection based on a minimal volume region

no code implementations • 6 Oct 2020 • Łukasz Maziarka, Marek Śmieja, Marcin Sendera, Łukasz Struski, Jacek Tabor, Przemysław Spurek

We propose OneFlow - a flow-based one-class classifier for anomaly (outlier) detection that finds a minimal volume bounding region.

Anomaly Detection One-class classifier

Data adaptation in HANDY economy-ideology model

no code implementations • 8 Apr 2019 • Marcin Sendera

However, despite their ability to better forecasting, the problem of an appropriate fitting ground truth data to those, high-dimensional and nonlinear models seems to be inevitable.