Research map / Probabilistic and scientific modeling / Variational and generative sampling
Z-Forcing: Training Stochastic Recurrent Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add the auxiliary cost to Ours (ablation) | Z-Forcing · Blizzard test | average log-likelihood per sequence: ≥ 14435 -> ≥ 15430 | Helped |
| Add the auxiliary cost to Ours (ablation) | Z-Forcing · TIMIT test | average log-likelihood per sequence: ≥ 68132 -> ≥ 69530 | Helped |
| Add KL annealing to Ours (ablation) | Z-Forcing · Blizzard test | average log-likelihood per sequence: ≥ 14435 -> ≥ 14226 | Hurt |
| Add KL annealing to Ours (ablation) | Z-Forcing · TIMIT test | average log-likelihood per sequence: ≥ 68132 -> ≥ 68903 | Helped |
| Add KL annealing alongside the auxiliary cost (ablation) | Z-Forcing · TIMIT test | average log-likelihood per sequence: ≥ 69530 -> ≥ 70469 | Helped |
| Add the auxiliary cost (ablation) | Z-Forcing · Sequential MNIST test | negative log-likelihood: ≤ 80.60 -> ≤ 80.09 | Helped |
| Use KL annealing (ablation) | Z-Forcing · Sequential MNIST | negative log-likelihood | Hurt |
| Add the auxiliary cost with α=0.0025 (ablation) | Z-Forcing · IMDB valid | word perplexity (ELBO): 53.93 -> 55.71 | Hurt |
| Add the auxiliary cost with α=0.0025 (ablation) | Z-Forcing · IMDB test | word perplexity (ELBO): 54.67 -> 56.57 | Hurt |
| Increase auxiliary-cost hyperparameter α from 0.0025 to 0.005 (ablation) | Z-Forcing with auxiliary cost · IMDB valid | word perplexity (ELBO): 55.71 -> 65.03 | Hurt |
| Increase auxiliary-cost hyperparameter α from 0.0025 to 0.005 (ablation) | Z-Forcing with auxiliary cost · IMDB test | word perplexity (ELBO): 56.57 -> 65.84 | Hurt |
| Train with the IWAE bound instead of the standard ELBO (ablation) | Z-Forcing · IMDB validation | perplexity | No clear effect |
Closest papers by meaning
- Sequential Neural Models with Stochastic Layers (NeurIPS 2016 · similarity 0.90)
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- Fast-Slow Recurrent Neural Networks (NeurIPS 2017 · similarity 0.88)
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- Variable Computation in Recurrent Neural Networks (ICLR 2017 · similarity 0.88)
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