Search Results for author: Georgios Exarchakis

Found 7 papers, 2 papers with code

A sampling-based approach for efficient clustering in large datasets

1 code implementation29 Dec 2021 Georgios Exarchakis, Omar Oubari, Gregor Lenz

We propose a simple and efficient clustering method for high-dimensional data with a large number of clusters.

ProSper -- A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions

no code implementations1 Aug 2019 Georgios Exarchakis, Jörg Bornschein, Abdul-Saboor Sheikh, Zhenwen Dai, Marc Henniges, Jakob Drefs, Jörg Lücke

The library widens the scope of dictionary learning approaches beyond implementations of standard approaches such as ICA, NMF or standard L1 sparse coding.

Dictionary Learning

Solid Harmonic Wavelet Scattering for Predictions of Molecule Properties

no code implementations1 May 2018 Michael Eickenberg, Georgios Exarchakis, Matthew Hirn, Stéphane Mallat, Louis Thiry

We present a machine learning algorithm for the prediction of molecule properties inspired by ideas from density functional theory.

Truncated Variational Sampling for "Black Box" Optimization of Generative Models

no code implementations21 Dec 2017 Jörg Lücke, Zhenwen Dai, Georgios Exarchakis

We investigate the optimization of two probabilistic generative models with binary latent variables using a novel variational EM approach.

Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities

no code implementations NeurIPS 2017 Michael Eickenberg, Georgios Exarchakis, Matthew Hirn, Stephane Mallat

We introduce a solid harmonic wavelet scattering representation, invariant to rigid motion and stable to deformations, for regression and classification of 2D and 3D signals.

General Classification

What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach

no code implementations NeurIPS 2013 Zhenwen Dai, Georgios Exarchakis, Jörg Lücke

By far most approaches to unsupervised learning learning of visual features, such as sparse coding or ICA, account for translations by representing the same features at different positions.

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