Publications

2021

Klemmer, K.*, Xu, T.*, Acciaio, B., Neill, Daniel D.B.
SPATE-GAN: Improved Generative Modeling of Dynamic Spatio-Temporal Patterns with an Autoregressive Embedding Loss
arXiv:2109.15044
[Paper] [Code]
Luo, M., Du B., Klemmer, K., Zhu, H., Wen, H.
Deployment Optimization for Shared e-Mobility Systems with Multi-agent Deep Neural Search
IEEE Transactions on Intelligent Transportation Systems (forthcoming)
[Paper]
Klemmer, K., Neill, D.B.
Auxiliary-task learning for geographic data with autoregressive embeddings
Conference Paper @ SIGSPATIAL'21
[Paper] [Code]
Reiersen, G., Dao, D., Lütjens, B., Klemmer, K., Zhu, X.X., Zhang, C.
Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery
Workshop Paper (Spotlight) @ ICML'21
[Paper]
Klemmer, K., Saha, S., Kahl, M., Xu, T., Zhu, X.X.
Generative modeling of spatio-temporal weather patterns with extreme event conditioning
Workshop Paper (Poster) @ ICLR'21
[Paper]
Klemmer, K., Neill, D.B., Jarvis, S.A.
Understanding Spatial Patterns in Rape Reporting Delays
Royal Society Open Science
[Paper]
Koshiyama, A., Kazim, E., Treleaven, P., Rai, P., Szpruch, L., Pavey, G., Ahamat, G., Leutner, F., Goebel, R., Knight, A, Adams, J., Hitrova, C., Barnett, J., Nachev, P., Barber, D., Chamorro-Premuzic, T., Klemmer, K., Gregorovic, M., Khan, S., Lomas, E.
Towards Algorithm Auditing: A Survey on Managing Legal, Ethical and Technological Risks of AI, ML and Associated Algorithms
SSRN Preprint [Paper]

2020

Luo, M., Du B., Klemmer, K., Zhu, H., Ferhatosmanoglu, H., Wen, H.
D3P: Data-Driven Demand Prediction for Fast Expanding Electric Vehicle Sharing Systems
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)
[Paper]
Klemmer, K., Yeboah, G., Porto de Albuquerque, J., Jarvis, S.A.
Population Mapping in Informal Settlements with High-Resolution Satellite Imagery and Equitable Ground-Truth
Workshop Paper (Poster) @ ICLR'20
[Paper]

2019

Klemmer, K., Koshiyama, A., Flennerhag S.
Augmenting Correlation Structures in Spatial Data Using Deep Generative Models
arXiv:1905.09796
[Paper] [Code] [Slides]
Luo, M., Wen, H., Luo, Y., Du, B., Klemmer, K., Zhu, H.
Demand Prediction for Electric Vehicle Sharing
arXiv:1903.04051
[Paper]

2018

Klemmer, K., Brandt, T., and Jarvis, S.A.
Isolating the effect of cycling on local business environments in London
PLOS ONE
[Paper] [Poster]
Klemmer, K., Neill, D.B., Jarvis, S.A.
Modeling Rape Reporting Delays Using Spatial, Temporal and Social Features
Workshop Paper (Oral) @ NeurIPS'18
[Paper] [Poster]
Munoz-Mendez, F.*, Klemmer, K.*, Han, K., Jarvis, S.A.
Community structures, interactions and dynamics in London’s bicycle sharing network
Workshop Paper (Oral) @ UbiComp'18
[Paper] [Code]

2017

Willing, C., Klemmer, K., Brandt, T., and Neumann, D.
Moving in Time and Space – Location Intelligence for Carsharing Decision Support
Decision Support Systems
[Paper]

2016

Klemmer, K., Willing, C., Wagner, S., and Brandt, T.
Explaining Spatio-Temporal Dynamics in Carsharing: A Case Study of Amsterdam
Conference Paper (Oral) @ AMCIS'16
[Paper]

* equal contribution

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