Journal and Conference Papers

2023

  • Xintong Shi, Wenzhi Cao, and Sebastian Raschka
    Deep Neural Networks for Rank-Consistent Ordinal Regression Based On Conditional Probabilities
    Pattern Analysis and Applications, Springer, 1433-755X
    [Journal Paper]
    [ArXiv Preprint] [PyTorch Implementation] [Experiment code]

  • Jiaxing Chen, Leslie A. Kuhn, and Sebastian Raschka
    Techniques for Developing Reliable Machine Learning Classifiers Applied to Understanding and Predicting Protein:Protein Interaction Hot Spots
    (Accepted for publication in Computational Drug Discovery and Design, Springer Methods in Molecular Biology series)
    [Bioarxiv Preprint] [GitHub Repo]

2022

  • Zhongjie Yu, Gaoang Wang, Lin Chen, Sebastian Raschka, Jiebo Luo
    When Few-Shot Learning Meets Video Object Detection
    ICPR 2022
    [ArXiv Preprint] [BibTex]

  • BD Lee, A Gitter, CS Greene, S Raschka, F Maguire, AJ Titus, MD Kessler, AJ Lee, MG Chevrette, PA Stewart, T Britto-Borges, EM Cofer, K-H Yu, JJ Carmona, EJ Fertig, AA Kalinin, B Signal, TJ Triche, Jr., SM Boca (2022).
    PLOS Computational Biology
    Ten Quick Tips for Deep Learning in Biology
    [Journal Link] [ArXiv Preprint] [GitHub Repo]

  • Kaiping Chen, Sang Jung Kim, Qiantong Gao, Sebastian Raschka (2022)
    Visual Framing of Science Conspiracy Videos: Integrating Machine Learning with Communication Theories to Study the Use of Color and Brightness
    Computational Communication Research, 4(1)
    [Journal Link] [ArXiv Preprint] [GitHub Repo]

2021

2020

2019

  • Vahid Mirjalili, Sebastian Raschka, and Arun Ross (2019)
    FlowSAN: Privacy-enhancing Semi-Adversarial Networks to Confound Arbitrary Face-based Gender Classifiers
    IEEE Access 2019, 10.1109/ACCESS.2019.2924619
    [Journal Paper] [ArXiv Preprint] [BibTex] [PDF (mirror)]

  • Sebastian Raschka (2019) Machine Learning-assisted Discovery of GPCR Bioactive Ligands
    Current Opinion in Structural Biology 2019, 55:17–24
    [Journal Paper] [ArXiv Preprint] [BibTex] [PDF (mirror)]

2018

  • Vahid Mirjalili, Sebastian Raschka, and Arun Ross (2018) Gender Privacy: An Ensemble of Semi Adversarial Networks for Confounding Arbitrary Gender Classifiers. 9th IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS 2018)
    [PDF] [ArXiV Preprint] [BibTex] [PDF (mirror)]

  • Sebastian Raschka, Shyam K. More, Dinesh Devadoss, Bixi Zeng, Leslie Kuhn, and Marc D. Basson (2018). Identification of potential small-molecule protein-protein inhibitors of cancer metastasis by 3D epitope-based computational screening. Journal of Physiology and Pharmacology 69, 2.
    [NIH Link] [Journal Paper] [BibTex] [PDF (mirror)]

  • Sebastian Raschka (2018) MLxtend: Providing Machine Learning and Data Science Utilities and Extensions to Python’s Scientific Computing Stack. The Journal of Open Source Software 3.24.
    [JOSS Link] [Code] [BibTex] [PDF (mirror)]

  • Vahid Mirjalili, Sebastian Raschka, Anoop Namboodiri, and Arun Ross (2018) Semi-adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images. Proc. of 11th IAPR International Conference on Biometrics (ICB 2018), Gold Coast, Australia. (Best Paper Award)
    [IEEE Link] [ArXiV Preprint] [Code] [BibTex] [Project Summary] [PDF (mirror)]

  • Sebastian Raschka, Alex Wolf, and Leslie A. Kuhn (2018) Protein-ligand Interfaces are Polarized: Discovery of a Strong Trend for Intermolecular Hydrogen Bonds to Favor Donors on the Protein Side with Implications for Predicting and Designing Ligand Complexes. Journal of Computer-Aided Molecular Design, 32(4), 511-528.
    [Springer Link] [Springer PDF] [BioRxiv Preprint] [Code] [BibTex] [PDF (mirror)]

  • Sebastian Raschka, Nan Liu, Santosh Gunturu, Anne M. Scott, Mar Huertas, Weiming Li, and Leslie A. Kuhn (2018) Facilitating the Hypothesis-driven Prioritization of Small Molecules in Large Databases: Screenlamp and its Application to GPCR Inhibitor Discovery. Journal of Computer-Aided Molecular Design, 32(3), 415-433.
    [Springer Link] [Springer PDF] [BioRxiv Preprint] [Code] [BibTex] [PDF (mirror)]

2017

  • Sebastian Raschka (2017) BioPandas: Working with Molecular Structures in Pandas DataFrames. The Journal of Open Source Software 2.14.
    [JOSS Link] [Code] [BibTex] [PDF (mirror)]

2016

  • Sebastian Raschka, Joseph Bemister-Buffington, and Leslie A. Kuhn (2016) Detecting the Native Ligand Orientation by Interfacial Rigidity: SiteInterlock. Proteins: Structure, Function and Bioinformatics 84.12: 1888-1901.
    [Wiley Link] [Wiley PDF] [Code] [BibTex] [PDF (mirror)]

Books

  • Sebastian Raschka, Yuxi (Hayden) Liu, Vahid Mirjalili. Machine Learning with PyTorch and Scikit-Learn. Birmingham, UK: Packt Publishing, 2022. ISBN: 978-1801819312
    [Amazon Link] [Code] [BibTex]
  • Sebastian Raschka, Vahid Mirjalili. Python Machine Learning. 3rd Edition. Birmingham, UK: Packt Publishing, 2019. ISBN: 978-1789955750
    [Amazon Link] [Code] [BibTex]
  • Sebastian Raschka, Vahid Mirjalili. Python Machine Learning. 2nd Edition. Birmingham, UK: Packt Publishing, 2017. ISBN: 978-3958457331
    [Amazon Link] [Code] [BibTex]
  • Sebastian Raschka, David Julian, and John Hearty. Python: Deeper Insights into Machine Learning. Birmingham, UK: Packt Publishing, 2016. ASIN: B01LD8K994
    [Packt Link]
  • Sebastian Raschka. Python Machine Learning. Birmingham, UK: Packt Publishing, 2015. ISBN: 978-1783555130. (Amazon bestseller in Data Mining 2015 & 2016, Packt bestselling title 2015 & 2016, more than; ACM Computing Reviews’ Notable Computing Books and Articles of 2016); translated into 7 different languages
    [Amazon Link] [Code] [BibTex]

  • Sebastian Raschka. Heat Maps in R: How-To. Birmingham, UK: Packt Publishing, 2013. ISBN: 978-1782165644
    [Amazon Link] [BibTex]

    Additional information and supporting materials are available on book page of my personal website https://sebastianraschka.com/books.

Translations of My Books into Other Languages

  • My books have been translated into more than 9 different languages. You can find a list here.

Book Chapters

  • Jiaxing Chen, Leslie A. Kuhn, and Sebastian Raschka (2023) Computational Drug Discovery and Design: Techniques for Developing Reliable Machine Learning Classifiers Applied to Understanding and Predicting Protein:Protein Interaction Hot Spots. Springer. ISBN 978-1-0716-3440-0
    [Springer Link] [Code] [Bioarxiv preprint]

  • Sebastian Raschka, Leslie A. Kuhn, Anne M. Scott, and Weiming Li (2018) Computational Drug Discovery and Design: Automated Inference of Chemical Group Discriminants of Biological Activity from Virtual Screening Data. Springer. ISBN: 978-1-4939-7755-0
    [Springer Link] [Code] [BibTex]

  • Mike Driscoll (ed.) (2018). Python Interviews: Discussions with prolific programmers. Packt Publishing Ltd. ISBN: 978-1-7883-9908-1
    [Amazon Link]

Technical Reports

  • Sebastian Raschka (2018). Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning.
    [Link]

  • Sebastian Raschka (2014). MusicMood: Predicting the mood of music from song lyrics using machine learning. arXiv:1611.00138.
    [Link]

  • Sebastian Raschka (2014). Naive Bayes and Text Classification I-Introduction and Theory. arXiv:1410.5329.
    [Link]

Patents

  • M.D. Basson, L.A. Kuhn, S. Raschka, “Inhibiting FAK-AKT Interaction to Inhibit Metastasis,” US patent application. Appl. No.: PCT/US2018/042919; Pub. No.: WO/2019/018666,

Journals and Special Issues