Sebastian Raschka

Publication Activity (10 Years)

Years Active: 2014-2023
Publications (10 Years): 30

Top Topics

Ordinal Regression

Machine Learning

Top Venues

J. Open Source Softw.

J. Comput. Aided Mol. Des.

Publications

Xintong Shi, Wenzhi Cao, Sebastian Raschka
Deep neural networks for rank-consistent ordinal regression based on conditional probabilities. Pattern Anal. Appl. 26 (3) (2023)
Benjamin D. Lee, Anthony Gitter, Casey S. Greene, Sebastian Raschka, Finlay Maguire, Alexander J. Titus, Michael D. Kessler, Alexandra J. Lee, Marc G. Chevrette, Paul Allen Stewart, Thiago Britto-Borges, Evan M. Cofer, Kun-Hsing Yu, Juan Jose Carmona, Elana J. Fertig, Alexandr A. Kalinin, Brandon Signal, Benjamin J. Lengerich, Timothy J. Triche Jr., Simina M. Boca
Ten quick tips for deep learning in biology. PLoS Comput. Biol. 18 (3) (2022)
Zhongjie Yu, Gaoang Wang, Lin Chen, Sebastian Raschka, Jiebo Luo
When Few-Shot Learning Meets Video Object Detection. ICPR (2022)
Xintong Shi, Wenzhi Cao, Sebastian Raschka
Deep Neural Networks for Rank-Consistent Ordinal Regression Based On Conditional Probabilities. CoRR (2021)
Sebastian Raschka
Deeper Learning By Doing: Integrating Hands-On Research Projects Into a Machine Learning Course. CoRR (2021)
Kaiping Chen, Sang Jung Kim, Sebastian Raschka, Qiantong Gao
Visual Framing of Science Conspiracy Videos: Integrating Machine Learning with Communication Theories to Study the Use of Color and Brightness. CoRR (2021)
Benjamin D. Lee, Anthony Gitter, Casey S. Greene, Sebastian Raschka, Finlay Maguire, Alexander J. Titus, Michael D. Kessler, Alexandra J. Lee, Marc G. Chevrette, Paul Allen Stewart, Thiago Britto-Borges, Evan M. Cofer, Kun-Hsing Yu, Juan Jose Carmona, Elana J. Fertig, Alexandr A. Kalinin, Beth Signal, Benjamin J. Lengerich, Timothy J. Triche Jr., Simina M. Boca
Ten Quick Tips for Deep Learning in Biology. CoRR (2021)
Sebastian Raschka
Deeper Learning By Doing: Integrating Hands-On Research Projects Into A Machine Learning Course. Teaching ML (2021)
Zhongjie Yu, Gaoang Wang, Lin Chen, Sebastian Raschka, Jiebo Luo
Few-Shot Learning for Video Object Detection in a Transfer-Learning Scheme. CoRR (2021)
Vahid Mirjalili, Sebastian Raschka, Arun Ross
PrivacyNet: Semi-Adversarial Networks for Multi-Attribute Face Privacy. IEEE Trans. Image Process. 29 (2020)
Sebastian Raschka, Joshua Patterson, Corey Nolet
Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence. Inf. 11 (4) (2020)
Sebastian Raschka, Joshua Patterson, Corey Nolet
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence. CoRR (2020)
Sebastian Raschka, Benjamin Kaufman
Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition. CoRR (2020)
Wenzhi Cao, Vahid Mirjalili, Sebastian Raschka
Rank consistent ordinal regression for neural networks with application to age estimation. Pattern Recognit. Lett. 140 (2020)
Zhongjie Yu, Sebastian Raschka
Looking Back to Lower-Level Information in Few-Shot Learning. Inf. 11 (7) (2020)
Vahid Mirjalili, Sebastian Raschka, Arun Ross
PrivacyNet: Semi-Adversarial Networks for Multi-attribute Face Privacy. CoRR (2020)
Zhongjie Yu, Sebastian Raschka
Looking back to lower-level information in few-shot learning. CoRR (2020)
Wenzhi Cao, Vahid Mirjalili, Sebastian Raschka
Consistent Rank Logits for Ordinal Regression with Convolutional Neural Networks. CoRR (2019)
Vahid Mirjalili, Sebastian Raschka, Arun Ross
FlowSAN: Privacy-enhancing Semi-Adversarial Networks to Confound Arbitrary Face-based Gender Classifiers. CoRR (2019)
Vahid Mirjalili, Sebastian Raschka, Arun Ross
FlowSAN: Privacy-Enhancing Semi-Adversarial Networks to Confound Arbitrary Face-Based Gender Classifiers. IEEE Access 7 (2019)
Sebastian Raschka, Alex J. Wolf, Joseph Bemister-Buffington, Leslie A. Kuhn
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. J. Comput. Aided Mol. Des. 32 (4) (2018)
Sebastian Raschka
Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning. CoRR (2018)
Sebastian Raschka, Anne M. Scott, Nan Liu, Santosh Gunturu, Mar Huertas, Weiming Li, Leslie A. Kuhn
Enabling the hypothesis-driven prioritization of ligand candidates in big databases: Screenlamp and its application to GPCR inhibitor discovery for invasive species control. J. Comput. Aided Mol. Des. 32 (3) (2018)
Vahid Mirjalili, Sebastian Raschka, Anoop M. Namboodiri, Arun Ross
Semi-adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images. ICB (2018)
Vahid Mirjalili, Sebastian Raschka, Arun Ross
Gender Privacy: An Ensemble of Semi Adversarial Networks for Confounding Arbitrary Gender Classifiers. BTAS (2018)
Vahid Mirjalili, Sebastian Raschka, Arun Ross
Gender Privacy: An Ensemble of Semi Adversarial Networks for Confounding Arbitrary Gender Classifiers. CoRR (2018)
Sebastian Raschka
MLxtend: Providing machine learning and data science utilities and extensions to Python's scientific computing stack. J. Open Source Softw. 3 (24) (2018)
Sebastian Raschka
BioPandas: Working with molecular structures in pandas DataFrames. J. Open Source Softw. 2 (14) (2017)
Vahid Mirjalili, Sebastian Raschka, Anoop M. Namboodiri, Arun Ross
Semi-Adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images. CoRR (2017)
Sebastian Raschka
MusicMood: Predicting the mood of music from song lyrics using machine learning. CoRR (2016)
Sebastian Raschka
An Overview of General Performance Metrics of Binary Classifier Systems. CoRR (2014)
Sebastian Raschka
Naive Bayes and Text Classification I - Introduction and Theory. CoRR (2014)