VAE-Info-cGAN: generating synthetic images by combining pixel-level and feature-level geospatial conditional inputs. - Xuerong Xiao; Swetava Ganguli; Vipul Pandey (IWCTS@SIGSPATIAL, 2020)

Trinity: A No-Code AI platform for complex spatial datasets. - C. V. Krishnakumar Iyer; Feili Hou; Henry Wang; Yonghong Wang; Kay Oh; Swetava Ganguli; Vipul Pandey (GeoAI@SIGSPATIAL, 2021)

Conditional Generation of Synthetic Geospatial Images from Pixel-level and Feature-level Inputs. - Xuerong Xiao; Swetava Ganguli; Vipul Pandey (CoRR, 2021)

Reachability Embeddings: Scalable Self-Supervised Representation Learning from Markovian Trajectories for Geospatial Computer Vision. - Swetava Ganguli; C. V. Krishnakumar Iyer; Vipul Pandey (CoRR, 2021)

Reachability Embeddings: Scalable Self-Supervised Representation Learning from Mobility Trajectories for Multimodal Geospatial Computer Vision. - Swetava Ganguli; C. V. Krishnakumar Iyer; Vipul Pandey (MDM, 2022)

Scalable Self-Supervised Representation Learning from Spatiotemporal Motion Trajectories for Multimodal Computer Vision. - Swetava Ganguli; C. V. Krishnakumar Iyer; Vipul Pandey (CoRR, 2022)

SeMAnD: Self-Supervised Anomaly Detection in Multimodal Geospatial Datasets. - Daria Reshetova; Swetava Ganguli; C. V. Krishnakumar Iyer; Vipul Pandey (SIGSPATIAL/GIS, 2023)

Self-Supervised Temporal Analysis of Spatiotemporal Data. - Yi Cao; Swetava Ganguli; Vipul Pandey (IGARSS, 2023)

Temporal Embeddings: Scalable Self-Supervised Temporal Representation Learning from Spatiotemporal Data for Multimodal Computer Vision. - Yi Cao; Swetava Ganguli; Vipul Pandey (CoRR, 2024)