Research map / Architectures and efficiency / RNNs and normalization
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Sawtooth Connection to couple topics across layers, rather than independent learned loadings (ablation) | SawETM · 20NG | AC: 49.25 -> 51.25 | Helped |
| Use Sawtooth Connection to couple topics across layers, rather than independent learned loadings (ablation) | SawETM · R8 | AC: 59.93 -> 63.82 | Helped |
| Share topic embeddings between adjacent layers through Sawtooth Connection (ablation) | SawETM · 20NG | NMI: 48.87 -> 50.77 | Helped |
| Share topic embeddings between adjacent layers through Sawtooth Connection (ablation) | SawETM · R8 | NMI: 44.12 -> 45.90 | Helped |
| Increase the number of layers beyond three | WHAI · Per-heldout-word perplexity | per-heldout-word perplexity | No clear effect |
| Increase the number of layers beyond three | DETM · Per-heldout-word perplexity | per-heldout-word perplexity | No clear effect |
| Increase the number of layers | SawETM · Per-heldout-word perplexity | per-heldout-word perplexity | Helped |
| Increase the number of layers | DETM · Topic quality | topic quality | Hurt |
Closest papers by meaning
- TopicNet: Semantic Graph-Guided Topic Discovery (NeurIPS 2021 · similarity 0.92)
- Dirichlet belief networks for topic structure learning (NeurIPS 2018 · similarity 0.89)
- Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network (NeurIPS 2020 · similarity 0.89)
- Bayesian Deep Embedding Topic Meta-Learner (ICML 2022 · similarity 0.89)
- Knowledge-Aware Bayesian Deep Topic Model (NeurIPS 2022 · similarity 0.88)
- On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling (AAAI 2024 · similarity 0.86)
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