Marion Neumann

According to our database, Marion Neumann authored at least 28 papers between 2009 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

EAAI-23 Blue Sky Ideas in Artificial Intelligence Education from the AAAI/ACM SIGAI New and Future AI Educator Program.

Michael Guerzhoy, Marion Neumann, Pat Virtue, Carolyn Jane Anderson, Yaman Kumar Singla, Alexi Orchard, Rajiv Ratn Shah

AI Matters, June, 2023

2022

EAAI-22 Blue Sky Ideas in Artificial Intelligence Education from the AAAI/ACM SIGAI New and Future AI Educator Program.

Michael Guerzhoy, Marion Neumann, Emmanuel Johnson, David Johnson, Henry Chai, Daniel Garijo, Zhuoyue Lyu, Christopher J. MacLellan

AI Matters, 2022

2021

Capturing Student Feedback and Emotions in Large Computing Courses: A Sentiment Analysis Approach.

Marion Neumann, Robin Linzmayer

Proceedings of the SIGCSE '21: The 52nd ACM Technical Symposium on Computer Science Education, 2021

2020

TUDataset: A collection of benchmark datasets for learning with graphs.

Christopher Morris, Nils M. Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, Marion Neumann

CoRR, 2020

Model AI Assignments 2020.

Todd W. Neller, Stephen Keeley, Michael Guerzhoy, Wolfgang Hönig, Jiaoyang Li, Sven Koenig, Ameet Soni, Krista Thomason, Lisa Zhang, Bibin Sebastian, Cinjon Resnick, Avital Oliver, Surya Bhupatiraju, Kumar Krishna Agrawal, James Allingham, Sejong Yoon, Jonathan Chen, Tom Larsen, Marion Neumann, Narges Norouzi, Ryan Hausen, Matthew Evett

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

A unifying view of explicit and implicit feature maps of graph kernels.

Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel

Data Min. Knowl. Discov., 2019

Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach.

Laura Antanas, Plinio Moreno, Marion Neumann, Rui Pimentel de Figueiredo, Kristian Kersting, José Santos-Victor, Luc De Raedt

Auton. Robots, 2019

AI education matters: a first introduction to modeling and learning using the data science workflow.

Marion Neumann

AI Matters, 2019

AI profiles: an interview with Leslie Kaelbling.

Marion Neumann

AI Matters, 2019

AI profiles: an interview with Thomas Dietterich.

Marion Neumann

AI Matters, 2019

ACM SIGAI activity report.

Sven Koenig, Sanmay Das, Rosemary D. Paradis, John P. Dickerson, Yolanda Gil, Katherine Guo, Benjamin Kuipers, Iolanda Leite, Hang Ma, Nicholas Mattei, Amy McGovern, Larry R. Medsker, Todd W. Neller, Marion Neumann, Plamen Petrov, Michael Rovatsos, David G. Stork

AI Matters, 2019

Model AI Assignments 2019.

Todd W. Neller, Raja Sooriamurthi, Michael Guerzhoy, Lisa Zhang, Paul Talaga, Christopher Archibald, Adam Summerville, Joseph C. Osborn, Cinjon Resnick, Avital Oliver, Surya Bhupatiraju, Kumar Krishna Agrawal, Nate Derbinsky, Elena Strange, Marion Neumann, Jonathan Chen, Zac Christensen, Michael Wollowski, Oscar Youngquist

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

AI profiles: an interview with Iolanda Leite.

Marion Neumann

AI Matters, 2018

AI profiles: an interview with Kristian Kersting.

Marion Neumann

AI Matters, 2018

An End-to-End Deep Learning Architecture for Graph Classification.

Muhan Zhang, Zhicheng Cui, Marion Neumann, Yixin Chen

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

A Unifying View of Explicit and Implicit Feature Maps for Structured Data: Systematic Studies of Graph Kernels.

Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel

CoRR, 2017

2016

Propagation kernels: efficient graph kernels from propagated information.

Marion Neumann, Roman Garnett, Christian Bauckhage, Kristian Kersting

Mach. Learn., 2016

2015

Learning with Graphs using Kernels from Propagated Information.

Marion Neumann

PhD thesis, 2015

pyGPs: a Python library for Gaussian process regression and classification.

Marion Neumann, Shan Huang, Daniel E. Marthaler, Kristian Kersting

J. Mach. Learn. Res., 2015

2014

Propagation Kernels.

Marion Neumann, Roman Garnett, Christian Bauckhage, Kristian Kersting

CoRR, 2014

High-level Reasoning and Low-level Learning for Grasping: A Probabilistic Logic Pipeline.

Laura Antanas, Plinio Moreno, Marion Neumann, Rui Pimentel de Figueiredo, Kristian Kersting, José Santos-Victor, Luc De Raedt

CoRR, 2014

Erosion Band Features for Cell Phone Image Based Plant Disease Classification.

Marion Neumann, Lisa Hallau, Benjamin Klatt, Kristian Kersting, Christian Bauckhage

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Explicit Versus Implicit Graph Feature Maps: A Computational Phase Transition for Walk Kernels.

Nils M. Kriege, Marion Neumann, Kristian Kersting, Petra Mutzel

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

2013

Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels.

Marion Neumann, Roman Garnett, Kristian Kersting

Proceedings of the Asian Conference on Machine Learning, 2013

2012

Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data.

Martin Schiegg, Marion Neumann, Kristian Kersting

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Efficient Graph Kernels by Randomization.

Marion Neumann, Novi Patricia, Roman Garnett, Kristian Kersting

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

2011

Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation.

Marion Neumann, Babak Ahmadi, Kristian Kersting

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2009

Stacked Gaussian Process Learning.

Marion Neumann, Kristian Kersting, Zhao Xu, Daniel Schulz

Proceedings of the ICDM 2009, 2009