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Inferring Latent Functions with Gaussian Processes in Differential Equations
Published on Feb 25, 20075288 Views
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Chapter list
Inferring Latent Functions with Gaussian Processes <br>in Differential Equations00:00
Advert!00:45
Gaussian Processes01:31
Application Overview01:47
Methodology02:35
Linear Response Model03:42
Linear Response Solution05:06
Covariance Functions - <br>Visualisation of RBF Covariance07:22
Covariance Samples07:53
Induced Covariance08:39
Covariance Result09:22
Cross Covariance10:13
Posterior for f10:40
Covariance for Transcription Model11:10
Joint Sampling of x (t) and f (t)12:00
Joint Sampling of x (t) and f (t)0112:29
Joint Sampling of x (t) and f (t)0213:52
Covariance for Transcription Model13:55
Noise Corruption14:06
Artificial Data Results14:39
Results16:22
Linear response analysis16:59
Linear Response Results17:03
Results Transcription Rates18:01
Results Transcription Rates0118:14
Results Transcription Rates0218:28
Linear Response Discussion18:35
Non-linear Response Model20:08
Formalism20:17
Example: linear response21:31
Oscillatory Behaviour<br> - Fix with MLP Covariance22:20
Covariance Samples23:11
Covariance Samples0123:17
Response Results24:13
Non-linear response analysis24:30
exp (·) Response Results25:35
log (1 + exp (f )) Response Results25:47
3<br>/1+exp(-f ) Response Results26:15
Discussion27:05
Other Relevant Work30:22
Open Question34:57