Set Functions for Time Series | ✓ Link | 86.99% | 0.22% | | | GRU-D | 2019-09-26 |
Interpolation-Prediction Networks for Irregularly Sampled Time Series | ✓ Link | 86.42% | 0.18% | | | IP-NETS | 2019-09-13 |
Set Functions for Time Series | ✓ Link | 86.28% | 0.35% | | | Transformer | 2019-09-26 |
Set Functions for Time Series | ✓ Link | 86.24% | 0.38% | | | IP-Nets | 2019-09-26 |
Multi-Time Attention Networks for Irregularly Sampled Time Series | ✓ Link | 85.8% | | | | mTAND-Full | 2021-01-25 |
Multi-Time Attention Networks for Irregularly Sampled Time Series | ✓ Link | 85.4% | | | | mTAND-Enc | 2021-01-25 |
Set Functions for Time Series | ✓ Link | 85.14% | 0.13% | | | SeFT-Attn | 2019-09-26 |
Recurrent Neural Networks for Multivariate Time Series with Missing Values | ✓ Link | 84.24% | 0.012% | | | GRU-D | 2016-06-06 |
Self-Supervised Transformer for Sparse and Irregularly Sampled Multivariate Clinical Time-Series | ✓ Link | 83.90% | | | | STraTS | 2021-07-29 |
Latent ODEs for Irregularly-Sampled Time Series | ✓ Link | 83.3% | 0.9% | | | ODE-RNN | 2019-07-08 |
Latent ODEs for Irregularly-Sampled Time Series | ✓ Link | 82.9% | 0.4% | | | Latent ODE (ODE enc | 2019-07-08 |
Latent ODEs for Irregularly-Sampled Time Series | ✓ Link | 82.6% | 0.7% | | | Latent ODE + Poisson | 2019-07-08 |
Set Functions for Time Series | ✓ Link | 81.69% | 0.43% | | | GRU-Simple | 2019-09-26 |
Set Functions for Time Series | ✓ Link | 79.94% | 1.17% | | | Phased-LSTM | 2019-09-26 |
[]() | | 78.7% | 1.4% | | | RNN ∆t | |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | 55.1 | | GRU-D - APC (n = 1) | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | 53.8 | | GRU-Simple | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | 53.7 | 0.863 | GRU-D [12] | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | 53.5 | | GRU-APC (n = 1) | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | 53.3 | | GRU-D - APC (n = 0) | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | 53.1 | | GRU-D | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | 52 | | GRU-Forward | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | 51.4 | | GRU | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | 50.4 | | GRU-APC (n = 0) | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | 50.3 | | GRU-Mean | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | | 0.85 | BRITS [4] | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | | 0.8424 | GRU-D [6] | 2021-06-29 |
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning | ✓ Link | | | | 0.834 | GRU-D [4] | 2021-06-29 |