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Spectral learning of linear dynamics from generalisedlinear observations with application to neural population data
Published on Jan 16, 20133161 Views
Latent linear dynamical systems with generalised-linear observation models arise in a variety of applications, for example when modelling the spiking activity of populations of neurons. Here, we sh
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Spectral Learning of Linear Dynamical Systems from Generalized-Linear Observations with Application to Neural Population Data00:00
Time series data - 100:24
Time series data - 200:43
Time series data - 300:47
Time series data - 400:51
State-space models for time series - 100:59
State-space models for time series - 201:26
State-space models for time series - 301:34
State-space models for time series - 401:42
Parameter estimation for gl-LDS using Expectation Maximization (EM) - 101:53
Parameter estimation for gl-LDS using Expectation Maximization (EM) - 202:27
Parameter estimation for gl-LDS using Expectation Maximization (EM) - 302:55
Parameter estimation for gl-LDS using Expectation Maximization (EM) - 403:19
A spectral method for LDS: Ho-Kalman method - 103:44
A spectral method for LDS: Ho-Kalman method - 203:54
A spectral method for LDS: Ho-Kalman method - 304:01
A spectral method for LDS: Ho-Kalman method - 404:07
A spectral method for LDS: Ho-Kalman method - 504:14
A spectral method for LDS: Ho-Kalman method - 604:21
A spectral method for LDS: Ho-Kalman method - 704:39
A spectral method for LDS: Ho-Kalman method - 805:02
A spectral method for LDS: Ho-Kalman method - 905:10
Moment matching for LDS with generalized-linear observations - 105:23
Moment matching for LDS with generalized-linear observations - 205:35
Moment matching for LDS with generalized-linear observations - 305:48
Moment matching for LDS with generalized-linear observations - 406:07
Moment matching for LDS with generalized-linear observations - 506:42
Moment matching for LDS with generalized-linear observations - 606:53
Moment matching for LDS with generalized-linear observations - 707:16
Moment matching for LDS with generalized-linear observations - 807:29
Moment matching for LDS with generalized-linear observations - 907:50
Spectral learning of LDS from GLM observations08:09
Experiments - 108:49
Experiments - 209:03
Experiments - 309:43
Experiments - 410:02
Artificial data sets sampled from ground truth Poisson LDS - 110:15
Artificial data sets sampled from ground truth Poisson LDS - 210:37
Artificial data sets sampled from ground truth Poisson LDS - 311:21
Artificial data sets sampled from ground truth Poisson LDS - 411:44
Results for multi-electrode recordings - 112:03
Results for multi-electrode recordings - 212:28
Results for multi-electrode recordings - 313:03
Results for multi-electrode recordings - 413:25
Results for multi-electrode recordings - 513:51
Extensions: external driving input - 114:09
Extensions: external driving input - 214:28
Extensions: external driving input - 314:30
Extensions: external driving input - 414:31
Summary - 115:04
Summary - 215:29
Summary - 315:41
Summary - 416:03