Antti Honkela
- Co-authors
- Magnus RattrayHarri ValpolaNeil D. LawrenceJuha KarhunenPei GaoJukka CoranderNiko VälimäkiTapani Raiko
- Topics
- Blind Source Separation Techniques (16 papers)Neural Networks and Applications (10 papers)Gene expression and cancer classification (9 papers)
- Partner nations
- FinlandUnited KingdomNorway
In The Last Decade
Antti Honkela
58 papers receiving 966 citations
Peers
Comparison fields: 5 of 123
- Molecular Biology 521
- Artificial Intelligence 263
- Genetics 135
- Signal Processing 115
- Cancer Research 72
Countries citing papers authored by Antti Honkela
This map shows the geographic impact of Antti Honkela'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 Antti Honkela with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Antti Honkela more than expected).
Fields of papers citing papers by Antti Honkela
This network shows the impact of papers produced by Antti Honkela. 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 Antti Honkela. The network helps show where Antti Honkela may publish in the future.
Co-authorship network of co-authors of Antti Honkela
This figure shows the co-authorship network connecting the top 25 collaborators of Antti Honkela. A scholar is included among the top collaborators of Antti Honkela 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 Antti Honkela. Antti Honkela is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 6 | |
| 3 | 28 | |
| 4 | Differentially Private Bayesian Inference for Generalized Linear Models | 4 |
| 5 | 2 | |
| 6 | Learning Rate Adaptation for Differentially Private Learning | 3 |
| 7 | Tight Approximate Differential Privacy for Discrete-Valued Mechanisms Using FFT. | 5 |
| 8 | Computing Tight Differential Privacy Guarantees Using FFT | 1 |
| 9 | Learning rate adaptation for differentially private stochastic gradient descent | 4 |
| 10 | 7 | |
| 11 | 121 | |
| 12 | 39 | |
| 13 | Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes | 48 |
| 14 | 4 | |
| 15 | Agglomerative Independent Variable Group Analysis. | 1 |
| 16 | Empirical evidence of the linear nature of magnetoencephalograms | 4 |
| 17 | Unsupervised Variational Bayesian Learning of Nonlinear Models | 31 |
| 18 | 33 | |
| 19 | Bayes Blocks Software Library | 5 |
| 20 | An Ensemble Learning Approach to Nonlinear Independent Component Analysis | 1 |
About Antti Honkela
Antti Honkela is a scholar working on Signal Processing, Artificial Intelligence and Statistics and Probability, having authored 61 papers that have together received 1.0k indexed citations. Recurring topics across this work include Blind Source Separation Techniques (16 papers), Neural Networks and Applications (10 papers) and Gene expression and cancer classification (9 papers). The work is most often cited by research in Signal Processing (115 citations), Artificial Intelligence (263 citations) and Molecular Biology (521 citations). Antti Honkela has collaborated with scholars based in Finland, United Kingdom and Norway. Frequent co-authors include Magnus Rattray, Harri Valpola, Neil D. Lawrence, Juha Karhunen, Pei Gao, Jukka Corander, Niko Välimäki, Tapani Raiko, Mikael Kuusela and Samuel Kaski. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Bioinformatics.
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.