Search Results for author: Hiroshi Morioka

Found 4 papers, 2 papers with code

Causal Representation Learning Made Identifiable by Grouping of Observational Variables

1 code implementation24 Oct 2023 Hiroshi Morioka, Aapo Hyvärinen

A topic of great current interest is Causal Representation Learning (CRL), whose goal is to learn a causal model for hidden features in a data-driven manner.

Causal Discovery Representation Learning

Nonlinear Independent Component Analysis for Principled Disentanglement in Unsupervised Deep Learning

no code implementations29 Mar 2023 Aapo Hyvarinen, Ilyes Khemakhem, Hiroshi Morioka

A central problem in unsupervised deep learning is how to find useful representations of high-dimensional data, sometimes called "disentanglement".

Disentanglement

Independent Innovation Analysis for Nonlinear Vector Autoregressive Process

no code implementations19 Jun 2020 Hiroshi Morioka, Hermanni Hälvä, Aapo Hyvärinen

Additivity greatly limits the generality of the model, hindering analysis of general NVAR processes which have nonlinear interactions between the innovations.

Time Series Time Series Analysis

Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA

2 code implementations NeurIPS 2016 Aapo Hyvarinen, Hiroshi Morioka

Nonlinear independent component analysis (ICA) provides an appealing framework for unsupervised feature learning, but the models proposed so far are not identifiable.

Contrastive Learning Time Series +1

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