Benjamin Bloem-Reddy

"I work on problems in statistics and machine learning, with an emphasis on probabilistic approaches. Some recent examples:

• Meaningful calibration of uncertainty in neural network models of conditional distributions and stochastic processes.
• Uses and benefits of symmetry in statistics, computation, and machine learning.
• Models and inference methods (SMC, MCMC) for evolving processes (e.g., networks) whose history is unobserved.

I also collaborate with researchers in the sciences on statistical problems arising in their research."