Marion Neumann

29 papers A* 6A 2B 1C 1Journal 17Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	EAAI-24 Blue Sky Ideas in Artificial Intelligence Education from the AAAI/ACM SIGAI New and Future AI Educator Program. AI Matters Marion Neumann, Stephanie Rosenthal, Justin Stevens, Rachel Lugo, William Agnew, Shira Wein
2023	J	`jnl`	EAAI-23 Blue Sky Ideas in Artificial Intelligence Education from the AAAI/ACM SIGAI New and Future AI Educator Program. AI Matters Michael Guerzhoy, Marion Neumann, Pat Virtue, Carolyn Jane Anderson, Yaman Kumar Singla, Alexi Orchard, Rajiv Ratn Shah
2022	J	`jnl`	EAAI-22 Blue Sky Ideas in Artificial Intelligence Education from the AAAI/ACM SIGAI New and Future AI Educator Program. AI Matters Michael Guerzhoy, Marion Neumann, Emmanuel Johnson, David Johnson, Henry Chai, Daniel Garijo, Zhuoyue Lyu, Christopher J. MacLellan
2021	A	`conf`	Capturing Student Feedback and Emotions in Large Computing Courses: A Sentiment Analysis Approach. SIGCSE Marion Neumann, Robin Linzmayer
2020	A*	`conf`	Model AI Assignments 2020. AAAI 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
2020	J	`jnl`	TUDataset: A collection of benchmark datasets for learning with graphs. CoRR Christopher Morris, Nils M. Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, Marion Neumann
2019	J	`jnl`	A unifying view of explicit and implicit feature maps of graph kernels. Data Min. Knowl. Discov. Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel
2019	J	`jnl`	ACM SIGAI activity report. AI Matters 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
2019	J	`jnl`	AI education matters: a first introduction to modeling and learning using the data science workflow. AI Matters Marion Neumann
2019	J	`jnl`	AI profiles: an interview with Leslie Kaelbling. AI Matters Marion Neumann
2019	J	`jnl`	AI profiles: an interview with Thomas Dietterich. AI Matters Marion Neumann
2019	A*	`conf`	Model AI Assignments 2019. AAAI Todd W. Neller, Raja Sooriamurthi, Michael Guerzhoy, Lisa Zhang, Paul G. 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
2019	J	`jnl`	Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach. Auton. Robots Laura Antanas, Plinio Moreno, Marion Neumann, Rui Pimentel de Figueiredo, Kristian Kersting, José Santos-Victor, Luc De Raedt
2018	J	`jnl`	AI profiles: an interview with Iolanda Leite. AI Matters Marion Neumann
2018	J	`jnl`	AI profiles: an interview with Kristian Kersting. AI Matters Marion Neumann
2018	A*	`conf`	An End-to-End Deep Learning Architecture for Graph Classification. AAAI Muhan Zhang, Zhicheng Cui, Marion Neumann, Yixin Chen
2017	J	`jnl`	A Unifying View of Explicit and Implicit Feature Maps for Structured Data: Systematic Studies of Graph Kernels. CoRR Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel
2016	J	`jnl`	Propagation kernels: efficient graph kernels from propagated information. Mach. Learn. Marion Neumann, Roman Garnett, Christian Bauckhage, Kristian Kersting
2015	—	`—`	Learning with Graphs using Kernels from Propagated Information. Marion Neumann
2015	J	`jnl`	pyGPs: a Python library for Gaussian process regression and classification. J. Mach. Learn. Res. Marion Neumann, Shan Huang, Daniel E. Marthaler, Kristian Kersting
2014	B	`conf`	Erosion Band Features for Cell Phone Image Based Plant Disease Classification. ICPR Marion Neumann, Lisa Hallau, Benjamin Klatt, Kristian Kersting, Christian Bauckhage
2014	A*	`conf`	Explicit Versus Implicit Graph Feature Maps: A Computational Phase Transition for Walk Kernels. ICDM Nils M. Kriege, Marion Neumann, Kristian Kersting, Petra Mutzel
2014	J	`jnl`	High-level Reasoning and Low-level Learning for Grasping: A Probabilistic Logic Pipeline. CoRR Laura Antanas, Plinio Moreno, Marion Neumann, Rui Pimentel de Figueiredo, Kristian Kersting, José Santos-Victor, Luc De Raedt
2014	J	`jnl`	Propagation Kernels. CoRR Marion Neumann, Roman Garnett, Christian Bauckhage, Kristian Kersting
2013	C	`conf`	Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels. ACML Marion Neumann, Roman Garnett, Kristian Kersting
2012	—	`conf`	Efficient Graph Kernels by Randomization. ECML/PKDD (1) Marion Neumann, Novi Patricia, Roman Garnett, Kristian Kersting
2012	A	`conf`	Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data. AISTATS Martin Schiegg, Marion Neumann, Kristian Kersting
2011	A*	`conf`	Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation. AAAI Marion Neumann, Babak Ahmadi, Kristian Kersting
2009	A*	`conf`	Stacked Gaussian Process Learning. ICDM Marion Neumann, Kristian Kersting, Zhao Xu, Daniel Schulz