jason71995 / Keras_ODENetLinks
Implementation of (2018) Neural Ordinary Differential Equations on Keras
☆65Updated 6 years ago
Alternatives and similar repositories for Keras_ODENet
Users that are interested in Keras_ODENet are comparing it to the libraries listed below
Sorting:
- Neural Ordinary Differential Equation☆101Updated 6 years ago
- [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs☆106Updated 4 years ago
- Sample implementation of Neural Ordinary Differential Equations☆263Updated 6 years ago
- Experiments with Neural Ordinary Differential Equations on image and text classification tasks☆31Updated 6 years ago
- Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support☆219Updated 4 years ago
- TensorFlow Probability Tutorial☆37Updated 5 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆140Updated 7 years ago
- Experiments with beta-VAE to learn disentangled representations from the data☆65Updated 6 years ago
- ☆59Updated 6 years ago
- Deep convolutional gaussian processes.☆79Updated 5 years ago
- An MDN Layer for Keras using TensorFlow's distributions module☆168Updated 11 months ago
- Kalman Variational Auto-Encoder☆136Updated 6 years ago
- Several implementations of the kernel-based activation functions☆62Updated 6 years ago
- Disentangled Variational Auto-Encoder in TensorFlow / Keras (Beta-VAE)☆54Updated 5 years ago
- Understanding normalizing flows☆132Updated 5 years ago
- Implementing Bayes by Backprop☆184Updated 6 years ago
- Pytorch implementation of Augmented Neural ODEs☆542Updated 2 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆119Updated 2 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆183Updated 6 years ago
- ☆115Updated last year
- Tensorflow implementation of Hyperspherical Variational Auto-Encoders☆232Updated 6 years ago
- ☆36Updated 2 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- ☆46Updated 2 years ago
- Neural Processes implementation for 1D regression☆65Updated 6 years ago
- ☆25Updated 2 years ago
- ☆28Updated 5 years ago
- Implementation of the Sliced Wasserstein Autoencoders☆91Updated 7 years ago
- Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)☆42Updated 5 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago