JSeam2 / Neural-Ordinary-Differential-EquationsLinks
Sample implementation of Neural Ordinary Differential Equations
☆262Updated 6 years ago
Alternatives and similar repositories for Neural-Ordinary-Differential-Equations
Users that are interested in Neural-Ordinary-Differential-Equations are comparing it to the libraries listed below
Sorting:
- Neural Ordinary Differential Equation☆102Updated 6 years ago
- [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs☆107Updated 4 years ago
- Guided Evolutionary Strategies☆272Updated 2 years ago
- Basic pytorch implementation of NAC/NALU from Neural Arithmetic Logic Units paper by trask et.al☆115Updated 6 years ago
- Tools for loading standard data sets in machine learning☆204Updated 2 years ago
- ICLR Reproducibility Challenge 2019☆217Updated 6 years ago
- ☆117Updated last year
- Implementation of Spectral Inference Networks, ICLR 2019☆172Updated 6 years ago
- Neural Architecture Search with Bayesian Optimisation and Optimal Transport☆135Updated 6 years ago
- Code for paper "L4: Practical loss-based stepsize adaptation for deep learning"☆124Updated 6 years ago
- A colab that implements the Symplectic Gradient Adjustment optimizer from "The mechanics of n-player differentiable games"☆153Updated 6 years ago
- Understanding normalizing flows☆132Updated 5 years ago
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆206Updated 6 years ago
- Implementation of Model-Agnostic Meta-Learning (MAML) in Jax☆191Updated 2 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆141Updated 9 years ago
- Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support☆223Updated 5 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆183Updated 7 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆361Updated 5 years ago
- Tensorflow Implementation of Interaction Networks for Learning about Objects, Relations and Physics☆158Updated 8 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- ☆133Updated 7 years ago
- Code for "Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer"☆244Updated 7 years ago
- Experiments with beta-VAE to learn disentangled representations from the data☆65Updated 6 years ago
- tutorial notebooks☆389Updated 7 years ago
- An implementation of KFAC for TensorFlow☆198Updated 3 years ago
- Implementation of (2018) Neural Ordinary Differential Equations on Keras☆66Updated 6 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Replicating "Understanding disentangling in β-VAE"☆199Updated 7 years ago
- Fast Scattering Transform with CuPy/PyTorch☆296Updated 5 years ago
- This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoe…☆206Updated 7 years ago