MIT-derived algorithm helps forecast the frequency of extreme weather
The new approach developed by researchers including SDSC faculty Themis Sapsis “nudges” existing climate simulations closer to future reality.
Dealing with the limitations of our noisy world
SDSC faculty Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.
New insights on political polarization
Researchers including SDSC faculty Teppei Yamamoto study the complexities of media preferences and partisan divides.
Automated method helps researchers quantify uncertainty in their predictions
An easy-to-use technique could assist everyone from economists to sports analysts, outlined in new paper from team including SDSC faculty Tamara ...
How symmetry can come to the aid of machine learning
MIT researchers including SDSC faculty Stefanie Jegelka show that exploiting the symmetry within datasets can decrease the amount of data needed ...
