| Tracking and Planning with Spatial World Models. | 0 | 0.34 | 2022 |
| Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF. | 0 | 0.34 | 2021 |
| Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models. | 0 | 0.34 | 2021 |
| Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models | 0 | 0.34 | 2021 |
| Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF | 0 | 0.34 | 2021 |
| Learning Flat Latent Manifolds with VAEs | 0 | 0.34 | 2020 |
| Bayesian Learning of Neural Network Architectures. | 0 | 0.34 | 2019 |
| Approximate Bayesian inference in spatial environments. | 1 | 0.35 | 2018 |
| Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data. | 6 | 0.45 | 2017 |
| Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data. | 0 | 0.34 | 2017 |
| Key Insights into Hand Biomechanics: Human Grip Stiffness Can Be Decoupled from Force by Cocontraction and Predicted from Electromyography. | 3 | 0.47 | 2017 |
| ML-based tactile sensor calibration: A universal approach. | 1 | 0.41 | 2016 |
| Variational Inference for On-line Anomaly Detection in High-Dimensional Time Series. | 10 | 0.64 | 2016 |
| Unsupervised preprocessing for Tactile Data. | 0 | 0.34 | 2016 |
| Theano: A Python framework for fast computation of mathematical expressions | 14 | 0.64 | 2016 |
| Efficient Empowerment. | 0 | 0.34 | 2015 |
| Fast Adaptive Weight Noise | 1 | 0.49 | 2015 |
| On Fast Dropout and its Applicability to Recurrent Networks | 0 | 0.34 | 2014 |
| Variational inference of latent state sequences using Recurrent Networks. | 0 | 0.34 | 2014 |
| Regularizing Recurrent Networks - On Injected Noise and Norm-based Methods. | 0 | 0.34 | 2014 |
| Learning Stochastic Recurrent Networks. | 44 | 2.20 | 2014 |
| Estimating finger grip force from an image of the hand using Convolutional Neural Networks and Gaussian processes | 1 | 0.36 | 2014 |
| Unsupervised Feature Learning for low-level Local Image Descriptors. | 0 | 0.34 | 2013 |
| Convolutional Neural Networks learn compact local image descriptors | 7 | 0.62 | 2013 |
| On Fast Dropout and its Applicability to Recurrent Networks. | 15 | 2.04 | 2013 |
| Computing Grip Force And Torque From Finger Nail Images Using Gaussian Processes | 0 | 0.34 | 2013 |
| Training Neural Networks with Implicit Variance. | 3 | 0.55 | 2013 |
| Continuous robot control using surface electromyography of atrophic muscles | 3 | 0.47 | 2013 |
| Unsupervised Feature Learning for low-level Local Image Descriptors | 2 | 0.39 | 2013 |
| Learning sequence neighbourhood metrics | 2 | 0.45 | 2012 |
| Identification of Human Limb Stiffness in 5 DoF and Estimation via EMG. | 0 | 0.34 | 2012 |
| PyBrain | 21 | 14.64 | 2010 |
| Evolving Memory Cell Structures for Sequence Learning | 23 | 1.81 | 2009 |
