JSeam2 / Neural-Ordinary-Differential-Equations
Sample implementation of Neural Ordinary Differential Equations
☆259Updated 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
- Neural Ordinary Differential Equation☆101Updated 6 years ago
- [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs☆103Updated 4 years ago
- Pytorch implementation of Augmented Neural ODEs☆537Updated 2 years ago
- Implementation of (2018) Neural Ordinary Differential Equations on Keras☆64Updated 5 years ago
- Understanding normalizing flows☆131Updated 5 years ago
- This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoe…☆206Updated 6 years ago
- Tools for loading standard data sets in machine learning☆203Updated 2 years ago
- code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".☆637Updated 4 years ago
- Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support☆218Updated 4 years ago
- Replicating "Understanding disentangling in β-VAE"☆197Updated 6 years ago
- Structured Inference Networks for Nonlinear State Space Models☆267Updated 7 years ago
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆206Updated 6 years ago
- ☆133Updated 7 years ago
- Implementation of Spectral Inference Networks, ICLR 2019☆171Updated 5 years ago
- Mathematics of Deep Learning, Courant Insititute, Spring 19☆275Updated 6 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆359Updated 5 years ago
- tutorial notebooks☆387Updated 6 years ago
- PyTorch implementation of Neural Processes☆88Updated 6 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- A colab that implements the Symplectic Gradient Adjustment optimizer from "The mechanics of n-player differentiable games"☆154Updated 6 years ago
- Code for "Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer"☆245Updated 6 years ago
- Neural Processes implementation for 1D regression☆65Updated 6 years ago
- Kalman Variational Auto-Encoder☆135Updated 6 years ago
- Code for paper "L4: Practical loss-based stepsize adaptation for deep learning"☆125Updated 5 years ago
- Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"☆378Updated 8 years ago
- Implementing Bayes by Backprop☆183Updated 5 years ago
- Neural Architecture Search with Bayesian Optimisation and Optimal Transport☆133Updated 6 years ago
- Dropout As A Bayesian Approximation: Code☆201Updated 9 years ago
- Implementation of Model-Agnostic Meta-Learning (MAML) in Jax☆188Updated 2 years ago