Research map / Probabilistic and scientific modeling / Variational and generative sampling
Self-Supervised Inference in State-Space Models
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Incorporate expert transition knowledge into self-supervised recursive inference | Recursive model · Linear dynamics | MSE: 0.241 -> 0.161 | Helped |
| Add RTS smoothing to the recursive filter (ablation) | Recursive Filter · SpeechCommands: Whitenoise | MSE: 0.107 -> 0.100 | Helped |
| Add RTS smoothing to the recursive filter (ablation) | Recursive Filter · SpeechCommands: Doing the dishes | MSE: 0.206 -> 0.204 | Helped |
| Add RTS smoothing to the recursive filter (ablation) | Recursive Filter · SpeechCommands: Dude miaowing | MSE: 0.213 -> 0.215 | Hurt |
| Add RTS smoothing to the recursive filter (ablation) | Recursive Filter · SpeechCommands: Exercise Bike | MSE: 0.198 -> 0.197 | Helped |
| Add RTS smoothing to the recursive filter (ablation) | Recursive Filter · SpeechCommands: Pink noise | MSE: 0.232 -> 0.231 | Helped |
| Add RTS smoothing to the recursive filter (ablation) | Recursive Filter · SpeechCommands: Running tap | MSE: 0.166 -> 0.166 | No clear effect |
| Add RTS smoothing to the recursive filter (ablation) | Recursive Filter · SpeechCommands: Combined | MSE: 0.175 -> 0.176 | Hurt |
| Use a recursive Bayesian filter rather than a directly parameterized recurrent filter | Recursive and recurrent models · Linear dynamics, low-data regime | MSE: 0.685 -> 0.161 | Helped |
| Use a recursive model rather than a recurrent model | Lorenz smoothing · Lorenz system | MSE | Helped |
| Apply linearized smoothing to recursive filtering distributions | Recursive Filter · Lorenz smoothing | MSE | Helped |
| Train with self-supervised recursive inference instead of Noise2Noise | SpeechCommands denoising · SpeechCommands noise classes | MSE | Helped |
Closest papers by meaning
- Gated Inference Network: Inference and Learning State-Space Models (NeurIPS 2024 · similarity 0.89)
- Structured Inference Networks for Nonlinear State Space Models (AAAI 2017 · similarity 0.89)
- Online Variational Filtering and Parameter Learning (NeurIPS 2021 · similarity 0.89)
- Linear approximations to HMM filtering (NeurIPS 2026 · similarity 0.88)
- Learning to Filter with Predictive State Inference Machines (ICML 2016 · similarity 0.88)
- Identifying latent state transitions in non-linear dynamical systems (ICLR 2025 · similarity 0.87)
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