Research map / Probabilistic and scientific modeling / Variational and generative sampling
Online Variational Filtering and Parameter Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the backward-factorized online variational method instead of AELBO-2 | Chaotic RNN state filtering · Chaotic RNN, d_x=5 | ELBO (nats): -30.944±2.2928 -> -15.845±1.7385 | Helped |
| Use the backward-factorized online variational method instead of AELBO-2 | Chaotic RNN state filtering · Chaotic RNN, d_x=20 | ELBO (nats): -393.68±3.9053 -> -340.36±3.9730 | Helped |
| Use the backward-factorized online variational method instead of AELBO-2 | Chaotic RNN state filtering · Chaotic RNN, d_x=100 | ELBO (nats): -2069.7±11.814 -> -1794.7±5.4173 | Helped |
| Use the backward-factorized online variational method instead of AELBO-2 | Chaotic RNN state filtering · Chaotic RNN, d_x=5 | Filter RMSE: 0.1026±0.0001 -> 0.1032±0.0005 | Mixed |
| Use the backward-factorized online variational method instead of AELBO-2 | Chaotic RNN state filtering · Chaotic RNN, d_x=20 | Filter RMSE: 0.1086±0.0004 -> 0.1082±0.0003 | Helped |
| Use the backward-factorized online variational method instead of AELBO-2 | Chaotic RNN state filtering · Chaotic RNN, d_x=100 | Filter RMSE: 0.1070±0.0001 -> 0.1068±0.0001 | Helped |
| Use the backward-factorized online variational method instead of AELBO-2 | Chaotic RNN state estimation · Chaotic RNN, d_x=5 | Filter mean RMSE: 0.0155±0.0006 -> 0.0128±0.0007 | Helped |
| Use the backward-factorized online variational method instead of AELBO-2 | Chaotic RNN state estimation · Chaotic RNN, d_x=5 | 1-step mean RMSE: 0.0241±0.0008 -> 0.0202±0.0009 | Helped |
Closest papers by meaning
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