| Scalable Bayesian nonparametric clustering and classification Y Ni, P Müller, M Diesendruck, S Williamson, Y Zhu, Y Ji Journal of Computational and Graphical Statistics 29 (1), 53-65, 2020 | 27 | 2020 |
| Importance weighted generative networks M Diesendruck, ER Elenberg, R Sen, GW Cole, S Shakkottai, ... Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020 | 21 | 2020 |
| BatchPrompt: Accomplish more with less J Lin, M Diesendruck, L Du, R Abraham arXiv preprint arXiv:2309.00384, 2023 | 7 | 2023 |
| Discovering distribution shifts using latent space representations L Betthauser, U Chajewska, M Diesendruck, R Pesala arXiv preprint arXiv:2202.02339, 2022 | 3 | 2022 |
| Data Visualization By Voice: Syntax, Parsing, and Recognition Techniques M Diesendruck, H Zhao | 2 | 2016 |
| Directing Generative Networks with Weighted Maximum Mean Discrepancy M Diesendruck, GW Cole, S Williamson | 1 | 2018 |
| Learning How To Ask: Cycle-Consistency Refines Prompts in Multimodal Foundation Models M Diesendruck, J Lin, S Imani, G Mahalingam, M Xu, J Zhao arXiv preprint arXiv:2402.08756, 2024 | | 2024 |
| Generating and presenting multi-dimensional representations for complex entities R Abraham, L Betthauser, Z Li, J Tian, X Zeng, M Diesendruck, ... US Patent 11,874,868, 2024 | | 2024 |
| Connection nature between nodes in graph structure LM Betthauser, M Diesendruck, H Shrivastava US Patent App. 18/244,440, 2023 | | 2023 |
| Generation and Explanation of Transformer Computation Graph Using Graph Attention Model LM Betthauser, M Diesendruck US Patent App. 17/840,169, 2023 | | 2023 |
| Determining concept relationships in document collections utilizing a sparse graph recovery machine-learning model H Shrivastava, M Diesendruck, R Abraham US Patent App. 17/833,142, 2023 | | 2023 |
| Generating real-time inferred network graphs H Shrivastava, M Diesendruck, R Abraham US Patent App. 17/833,221, 2023 | | 2023 |
| Connection nature between nodes in graph structure LM Betthauser, M Diesendruck, H Shrivastava US Patent 11,797,580, 2023 | | 2023 |
| Systems and methods for generating object state distributions usable for image comparison tasks M Diesendruck, R Abraham US Patent 11,748,973, 2023 | | 2023 |
| Systems and methods for utilizing object state distributions for image comparison tasks M Diesendruck, R Abraham US Patent App. 17/554,777, 2023 | | 2023 |
| Discovering distribution shifts in embeddings LM Betthauser, US Chajewska, M Diesendruck, RV Pesala US Patent App. 17/556,642, 2023 | | 2023 |
| Intelligent machine-learning model catalog LM Betthauser, US Chajewska, M Diesendruck, HHLR Pan, RV Pesala US Patent App. 17/556,648, 2023 | | 2023 |
| Graph Based Discovery on Deep Learning Embeddings R Abraham, LM Betthauser, M Diesendruck, US Chajewska US Patent App. 17/389,039, 2023 | | 2023 |
| Distribution Distance Measures in Generative and Privacy Models M Diesendruck The University of Texas at Austin, 2019 | | 2019 |
Sinead WilliamsonAssistant professor, University of Texas at AustinVerified email at mccombs.utexas.edu
