Aapo Hyvärinen
About
In The Last Decade
Aapo Hyvärinen
179 papers receiving 24.9k citations
Hit Papers
Peers
Comparison fields: 5 of 204
- Signal Processing 13.1k
- Cognitive Neuroscience 8.8k
- Artificial Intelligence 6.2k
- Analytical Chemistry 4.8k
- Computer Vision and Pattern Recognition 4.1k
Countries citing papers authored by Aapo Hyvärinen
This map shows the geographic impact of Aapo Hyvärinen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Aapo Hyvärinen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aapo Hyvärinen more than expected).
Fields of papers citing papers by Aapo Hyvärinen
This network shows the impact of papers produced by Aapo Hyvärinen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Aapo Hyvärinen. The network helps show where Aapo Hyvärinen may publish in the future.
Co-authorship network of co-authors of Aapo Hyvärinen
This figure shows the co-authorship network connecting the top 25 collaborators of Aapo Hyvärinen. A scholar is included among the top collaborators of Aapo Hyvärinen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Aapo Hyvärinen. Aapo Hyvärinen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 3 | |
| 3 | ICE-BeeM: Identifiable Conditional Energy-Based Deep Models. | 2 |
| 4 | Density Estimation in Infinite Dimensional Exponential Families | 16 |
| 5 | Unsupervised feature extraction by time-contrastive learning and nonlinear ICA | 46 |
| 6 | Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations | 1 |
| 7 | Learning a selectivity--invariance--selectivity feature extraction architecture for images | 2 |
| 8 | 313 | |
| 9 | A general linear non-Gaussian state-space model: Identifiability, identification, and applications | 7 |
| 10 | Structural equations and divisive normalization for energy-dependent component analysis | 4 |
| 11 | 168 | |
| 12 | Pairwise Measures of Causal Direction in Linear Non-Gaussian Acyclic Models | 14 |
| 13 | Learning reconstruction and prediction of natural stimuli by a population of spiking neurons | 0 |
| 14 | Modelling image complexity by independent component analysis, with application to content-based image retrieval | 5 |
| 15 | FastISA: A fast fixed-point algorithm for Independent Subspace Analysis | 30 |
| 16 | Estimation of Non-Normalized Statistical Models by Score Matching | 351 |
| 17 | Discovery of non-gaussian linear causal models using ICA | 15 |
| 18 | Temporal Coherence, Natural Image Sequences, and the Visual Cortex | 11 |
| 19 | Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA | 23 |
| 20 | One-unit Learning Rules for Independent Component Analysis | 32 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.