Multidimensional hourglass filter banks decompose the frequency spectrum of input signals into hourglass-shaped directional subbands, each aligned with one of the frequency axes. T...
We represent time-varying data as polyline charts very often. At the same time, we often need to observe hundreds or even thousands of time-varying values in one chart. However, i...
State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreir...
Traditional "realistic" theories of social action, whether based on the individual gain heuristics of capitalism or the collective class struggles of communism, cannot e...
This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...