no code implementations • 27 Jun 2023 • Dionysis Manousakas, Sergül Aydöre
Despite recent advances in synthetic data generation, the scientific community still lacks a unified consensus on its usefulness.
1 code implementation • 4 Nov 2022 • Dionysis Manousakas, Hippolyt Ritter, Theofanis Karaletsos
Recent advances in coreset methods have shown that a selection of representative datapoints can replace massive volumes of data for Bayesian inference, preserving the relevant statistical information and significantly accelerating subsequent downstream tasks.
1 code implementation • NeurIPS 2020 • Dionysis Manousakas, Zuheng Xu, Cecilia Mascolo, Trevor Campbell
Standard Bayesian inference algorithms are prohibitively expensive in the regime of modern large-scale data.
1 code implementation • 31 Aug 2020 • Dionysis Manousakas, Cecilia Mascolo
Modern machine learning applications should be able to address the intrinsic challenges arising over inference on massive real-world datasets, including scalability and robustness to outliers.