Abstract: Wasserstein barycenters have become a central object in applied optimal transport as a tool to summarize complex objects that can be represented as distributions. Such objects include posterior distributions in Bayesian statistics, functions in functional data analysis and images in graphics. In a nutshell a Wasserstein barycenter is a probability distribution that provides a…
Please join us on Tuesday, April 6, 2021 at 3:00pm for the Distinguished Speaker Seminar with Jens Hainmueller (Stanford University).
Abstract: The magnitude of the weights of a neural network is a fundamental measure of complexity that plays a crucial role in the study of implicit and explicit regularization. For example, in recent work, gradient descent updates in overparameterized models asymptotically lead to solutions that implicitly minimize the ell_2 norm of the parameters of the…
The potential of AI to bring equity in healthcare has spurred significant research efforts across academia, industry and government. Racial, gender and socio-economic disparities have traditionally afflicted healthcare systems in ways that are difficult to detect and quantify. New AI technologies, however, provide a platform for change.
Abstract: Sequential Multiple Assignment Randomized Trials (SMARTs) are considered the gold standard for estimation and evaluation of treatment regimes. SMARTs are typically sized to ensure sufficient power for a simple comparison, e.g., the comparison of two fixed treatment sequences. Estimation of an optimal treatment regime is conducted as part of a secondary and hypothesis-generating analysis…
Abstract: Prioritizing likely causal genes from genome-wide association studies (GWAS) is a fundamental problem. There are many methods for GWAS gene prioritization, including methods that map candidate SNPs to their target genes and methods that leverage patterns of enrichment from across the genome. In this talk, I will introduce a new method for leveraging genome-wide patterns of…
The Paths from Research to Impact workshop brings together a breadth of experts to highlight how data-driven research on COVID-19 has informed policy decisions and impacted the pandemic response on both local and global scales.
Abstract: Wasserstein barycenters have become a central object in applied optimal transport as a tool to summarize complex objects that can be represented as distributions. Such objects include posterior distributions in Bayesian statistics, functions in functional data analysis and images in graphics. In a nutshell a Wasserstein barycenter is a probability distribution that provides a…
Please join us on Tuesday, April 6, 2021 at 3:00pm for the Distinguished Speaker Seminar with Jens Hainmueller (Stanford University).
Abstract: The magnitude of the weights of a neural network is a fundamental measure of complexity that plays a crucial role in the study of implicit and explicit regularization. For example, in recent work, gradient descent updates in overparameterized models asymptotically lead to solutions that implicitly minimize the ell_2 norm of the parameters of the…
The potential of AI to bring equity in healthcare has spurred significant research efforts across academia, industry and government. Racial, gender and socio-economic disparities have traditionally afflicted healthcare systems in ways that are difficult to detect and quantify. New AI technologies, however, provide a platform for change.
Abstract: Sequential Multiple Assignment Randomized Trials (SMARTs) are considered the gold standard for estimation and evaluation of treatment regimes. SMARTs are typically sized to ensure sufficient power for a simple comparison, e.g., the comparison of two fixed treatment sequences. Estimation of an optimal treatment regime is conducted as part of a secondary and hypothesis-generating analysis…
Abstract: Prioritizing likely causal genes from genome-wide association studies (GWAS) is a fundamental problem. There are many methods for GWAS gene prioritization, including methods that map candidate SNPs to their target genes and methods that leverage patterns of enrichment from across the genome. In this talk, I will introduce a new method for leveraging genome-wide patterns of…
The Paths from Research to Impact workshop brings together a breadth of experts to highlight how data-driven research on COVID-19 has informed policy decisions and impacted the pandemic response on both local and global scales.
