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A century later, it was an abandoned building with an uncertain future. From cornerstone to keystone, from the first director to the people who saved it from destruction, explore the life of a historic observatory 170 years in the making.\n\n\"Watcher of the Sky\" is being developed by student docents at the Detroit Observatory. Presented by the Judy and Stanley Frankel Detroit Observatory, part of the Bentley Historical Library.\n\n\"Watcher of the Sky\" is now on display at the Detroit Observatory (1398 Ann Street, Ann Arbor, 48109). 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Join us as we celebrate our graduates during CLASP Commencement at 1:00pm, Friday, May 1, 2026. The commencement ceremony on campus will be followed by a reception with dessert and light refreshments at the Leinweber Innovation Laboratory in the Climate and Space Research Building (CSRB 1236). Streaming of the ceremony will also be available live on YouTube.\n\nIf you plan to attend in person, please RSVP at the link.", "occurrence_notes":"A reception will follow in the Leinweber Innovation Laboratory (CSRB 1236)", "guid":"147532-21901207@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/147532", "building_id":"1005418", "building_name":"Ford Robotics Building", "campus_maps_id":"647", "room":"1060", "location_name":"Ford Robotics Building", "has_livestream":0, "cost":"", "tags":["Climate and Space Sciences and Engineering"], "website":"https:\/\/docs.google.com\/forms\/d\/e\/1FAIpQLSd1mz3YRSnsRh4476iiw2JDHZa5yVI4bO91WXYsKf8i1hdHjw\/viewform", "sponsors":[ { "group_name":"Climate and Space Sciences and Engineering", "group_id":"3320", "website":"http:\/\/aoss.engin.umich.edu\/" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2026\/04\/event_147532_original-1.jpg", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_thumb\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "event_large":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_large\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "event_large_2x":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_large_2x\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "event_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/event_large_lightbox\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "group_thumb":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_thumb\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "group_thumb_square":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_thumb_square\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "group_large":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_large\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "group_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_large_lightbox\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "event_large_crop":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_large_crop\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "event_list":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_list\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "event_list_2x":"https:\/\/events.umich.edu\/media\/cache\/event_list_2x\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "event_grid":"https:\/\/events.umich.edu\/media\/cache\/event_grid\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "event_grid_2x":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_grid_2x\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "event_feature_large":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_feature_large\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg", "event_feature_thumb":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_feature_thumb\/media\/attachments\/2026\/04\/crop-event_147532_original-1.jpg" }, "occurrence_count":1, "first_occurrence":21901207 } , "141325-21901499": { "datetime_modified":"20260413T104859", "datetime_start":"20260501T130000", "datetime_end":"20260501T134500", "has_end_time":1, "date_start":"2026-05-01", "date_end":"2026-05-01", "time_start":"13:00:00", "time_end":"13:45:00", "time_zone":"America\/Detroit", "event_title":"Sky Tonight", "occurrence_title":"", "combined_title":"Sky Tonight", "event_subtitle":"", "event_type":"Exhibition", "event_type_id":"7", "description":"A live presentation on what to find in the sky tonight and for the coming few weeks. This presentation includes how to find the cardinal directions with the North Star, current and upcoming constellations, visible planets, a few deep sky objects depending on the season, and other interesting astronomical visualizations. 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Traditional analytical methods for relational data primarily focus on pairwise relations; however, real-world interactions often involve more than two entities and are inherently multi-way. In current practice, these multi-way interactions are typically projected into pairwise relations before analysis, which causes substantial information loss. Directly studying hypergraphs, which naturally encode general multi-way interactions, allows for more effective information extraction from such relational data.\n\nThis thesis develops efficient embedding and generative modeling frameworks for hypergraph data. The first part of the thesis introduces a general latent embedding framework that overcomes key limitations of existing hypergraph modeling methods. We establish identifiability of the latent embedding space and develop a likelihood-based estimator for the latent embeddings. We further derive consistency guarantees and asymptotic distributions for the parameter estimates, enabling efficient inference from an observed hypergraph. Building on these results, the second part of the thesis develops Denoising Diffused Embeddings (DDE), a generative architecture for hypergraphs that produces new hyperlinks not seen in the observed data. DDE connects discrete hyperlinks to a continuous latent space through a conditional hyperlink likelihood model and then reconstructs that space using a denoising diffusion process. Compared with existing generative models, DDE is computationally efficient to train and sample from, and it offers interpretability from the likelihood perspective. Our theoretical and empirical studies demonstrate its advantages as a general generative modeling framework. The third part of the thesis further extends this line of work to hypergraphs with hyperlink attributes. We propose ReLaSH, a generative framework that first learns a likelihood-based joint latent space for hyperlinks and their attributes and then reconstructs this space using a flexible distribution-free generator, enabling the generation of realistic synthetic attributed hypergraphs. We demonstrate the consistency and generalizability of ReLaSH through both theoretical analysis and simulation studies. Empirical results on a range of real-world datasets from diverse domains further demonstrate the strong performance of ReLaSH in comparison with other baselines, underscoring its broad utility and effectiveness in practical applications. 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