Explaining Spatio-Temporal Dynamics in Carsharing: A Case Study of Amsterdam. - Konstantin Klemmer; Christoph Willing; Sebastian Wagner 004; Tobias Brandt (AMCIS, 2016)

Moving in time and space - Location intelligence for carsharing decision support. - Christoph Willing; Konstantin Klemmer; Tobias Brandt; Dirk Neumann 001 (Decis. Support Syst., 2017)

Community Structures, Interactions and Dynamics in London's Bicycle Sharing Network. - Fernando Munoz-Mendez; Ke Han; Konstantin Klemmer; Stephen A. Jarvis (UbiComp/ISWC Adjunct, 2018)

Modeling Rape Reporting Delays Using Spatial, Temporal and Social Features. - Konstantin Klemmer; Daniel B. Neill; Stephen A. Jarvis (CoRR, 2018)

Dynamic Demand Prediction for Expanding Electric Vehicle Sharing Systems: A Graph Sequence Learning Approach. - Man Luo 001; Hongkai Wen 001; Yi Luo; Bowen Du 002; Konstantin Klemmer; Hongming Zhu (CoRR, 2019)

Augmenting correlation structures in spatial data using deep generative models. - Konstantin Klemmer; Adriano S. Koshiyama; Sebastian Flennerhag (CoRR, 2019)

SXL: Spatially explicit learning of geographic processes with auxiliary tasks. - Konstantin Klemmer; Daniel B. Neill (CoRR, 2020)

Population Mapping in Informal Settlements with High-Resolution Satellite Imagery and Equitable Ground-Truth. - Konstantin Klemmer; Godwin Yeboah; João Porto de Albuquerque; Stephen A. Jarvis (CoRR, 2020)

D3P: Data-driven Demand Prediction for Fast Expanding Electric Vehicle Sharing Systems. - Man Luo 001; Bowen Du 002; Konstantin Klemmer; Hongming Zhu; Hakan Ferhatosmanoglu; Hongkai Wen 001 (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020)

Auxiliary-task learning for geographic data with autoregressive embeddings. - Konstantin Klemmer; Daniel B. Neill (SIGSPATIAL/GIS, 2021)

Proceedings of the NeurIPS 2020 Workshop on Machine Learning for the Developing World: Improving Resilience. - Tejumade Afonja; Konstantin Klemmer; Aya Salama 001; Paula Rodriguez Diaz; Niveditha Kalavakonda; Oluwafemi Azeez (CoRR, 2021)

Generative modeling of spatio-temporal weather patterns with extreme event conditioning. - Konstantin Klemmer; Sudipan Saha; Matthias Kahl; Tianlin Xu; Xiao Xiang Zhu 001 (CoRR, 2021)

Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery. - Gyri Reiersen; David Dao; Björn Lütjens; Konstantin Klemmer; Xiaoxiang Zhu 001; Ce Zhang 001 (CoRR, 2021)

SPATE-GAN: Improved Generative Modeling of Dynamic Spatio-Temporal Patterns with an Autoregressive Embedding Loss. - Konstantin Klemmer; Tianlin Xu; Beatrice Acciaio; Daniel B. Neill (AAAI, 2022)

ReforesTree: A Dataset for Estimating Tropical Forest Carbon Stock with Deep Learning and Aerial Imagery. - Gyri Reiersen; David Dao; Björn Lütjens; Konstantin Klemmer; Kenza Amara; Attila Steinegger; Ce Zhang 001; Xiaoxiang Zhu 001 (AAAI, 2022)

GeoPointGAN: Synthetic Spatial Data with Local Label Differential Privacy. - Teddy Cunningham; Konstantin Klemmer; Hongkai Wen 001; Hakan Ferhatosmanoglu (CoRR, 2022)

Deployment Optimization for Shared e-Mobility Systems With Multi-Agent Deep Neural Search. - Man Luo 001; Bowen Du 002; Konstantin Klemmer; Hongming Zhu; Hongkai Wen 001 (IEEE Trans. Intell. Transp. Syst., 2022)

Improving neural networks for geospatial applications with geographic context embeddings. - Konstantin Klemmer (2022)

Positional Encoder Graph Neural Networks for Geographic Data. - Konstantin Klemmer; Nathan S. Safir; Daniel B. Neill (AISTATS, 2023)

Proceedings of the NeurIPS 2021 Workshop on Machine Learning for the Developing World: Global Challenges. - Paula Rodriguez Diaz; Tejumade Afonja; Konstantin Klemmer; Aya Salama 001; Niveditha Kalavakonda; Oluwafemi Azeez; Simone Fobi (CoRR, 2023)

Reflections from the Workshop on AI-Assisted Decision Making for Conservation. - Lily Xu; Esther Rolf; Sara Beery; Joseph R. Bennett; Tanya Y. Berger-Wolf; Tanya Birch; Elizabeth Bondi-Kelly; Justin Brashares; Melissa S. Chapman; Anthony Corso 001; Andrew Davies; Nikhil Garg; et al. (CoRR, 2023)

Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks. - Marc Rußwurm; Konstantin Klemmer; Esther Rolf; Robin Zbinden; Devis Tuia (ICLR, 2024)

Position: Mission Critical - Satellite Data is a Distinct Modality in Machine Learning. - Esther Rolf; Konstantin Klemmer; Caleb Robinson; Hannah Kerner (ICML, 2024)

Mission Critical - Satellite Data is a Distinct Modality in Machine Learning. - Esther Rolf; Konstantin Klemmer; Caleb Robinson; Hannah Kerner (CoRR, 2024)

Unveiling Patterns of the Earth through Machine Learning and Geospatial Analysis. - Jiayi Li; Konstantin Klemmer (XRDS, 2024)

SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery. - Konstantin Klemmer; Esther Rolf; Caleb Robinson; Lester Mackey; Marc Rußwurm (AAAI, 2025)