Sebastian Raschka
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Molecular Biology
- Signal Processing top 5%
- Computational Theory and Mathematics top 5%
- Co-authors
- Vahid MirjaliliWenzhi CaoArun RossLeslie A. KuhnKaiping ChenSang Jung KimDinesh DevadossMar Huertas
- Topics
- Computational Drug Discovery Methods (8 papers)Face recognition and analysis (6 papers)Protein Structure and Dynamics (4 papers)
- Journals
- IEEE Transactions on Image ProcessingIEEE AccessProteins Structure Function and Bioinformatics
- Partner nations
- United States
In The Last Decade
Sebastian Raschka
22 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 192
- Artificial Intelligence 350
- Computer Vision and Pattern Recognition 295
- Molecular Biology 240
- Signal Processing 161
- Computational Theory and Mathematics 149
Countries citing papers authored by Sebastian Raschka
This map shows the geographic impact of Sebastian Raschka'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 Sebastian Raschka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sebastian Raschka more than expected).
Fields of papers citing papers by Sebastian Raschka
This network shows the impact of papers produced by Sebastian Raschka. 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 Sebastian Raschka. The network helps show where Sebastian Raschka may publish in the future.
Co-authorship network of co-authors of Sebastian Raschka
This figure shows the co-authorship network connecting the top 25 collaborators of Sebastian Raschka. A scholar is included among the top collaborators of Sebastian Raschka 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 Sebastian Raschka. Sebastian Raschka is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 12 | |
| 3 | 63 | |
| 4 | 24 | |
| 5 | 79 | |
| 6 | 134 | |
| 7 | Rank Consistent Logits for Ordinal Regression with Convolutional Neural Networks | 1 |
| 8 | Rank-consistent Ordinal Regression for Neural Networks | 16 |
| 9 | 14 | |
| 10 | 33 | |
| 11 | 45 | |
| 12 | 14 | |
| 13 | MLxtend: Providing machine learning and data science utilities and extensions to Python’s scientific computing stackbreakdown → | 419 |
| 14 | 32 | |
| 15 | 5 | |
| 16 | 8 | |
| 17 | Python machine learning : machine learning and deep learning with Python, scikit-learn, and TensorFlow | 141 |
| 18 | 42 | |
| 19 | Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics | 31 |
| 20 | Python Machine Learningbreakdown → | 421 |
About Sebastian Raschka
Sebastian Raschka is a scholar working on Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 23 papers that have together received 1.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Face recognition and analysis (6 papers) and Protein Structure and Dynamics (4 papers). The work is most often cited by research in Signal Processing (161 citations), Computer Vision and Pattern Recognition (295 citations) and Artificial Intelligence (350 citations). Sebastian Raschka has collaborated with scholars based in United States. Frequent co-authors include Vahid Mirjalili, Wenzhi Cao, Arun Ross, Leslie A. Kuhn, Kaiping Chen, Sang Jung Kim, Dinesh Devadoss, Mar Huertas, Weiming Li and Marc D. Basson. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Access and Proteins Structure Function 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.