shz9 / csc2541-ml-project
Modeling Uncertainty in RNNs for Time Series Forecasting
☆14Updated 7 years ago
Alternatives and similar repositories for csc2541-ml-project:
Users that are interested in csc2541-ml-project are comparing it to the libraries listed below
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- TensorFlow Probability Tutorial☆37Updated 5 years ago
- ☆29Updated 5 years ago
- Parametric Gaussian Process Regression for Big Data☆44Updated 5 years ago
- Clean repo for tensor-train RNN implemented in TensorFlow☆69Updated 5 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Implementation of RNN for Time Series prediction from the paper https://arxiv.org/abs/1704.02971☆59Updated 2 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Learning error bars for neural network predictions☆70Updated 5 years ago
- Gaussian processes with PyTorch☆30Updated 3 years ago
- State space modeling with recurrent neural networks☆45Updated 7 years ago
- MLSS2019 Tutorial on Bayesian Deep Learning☆91Updated 5 years ago
- Python implementation of the PR-SSM.☆51Updated 6 years ago
- Multi-Information Source Optimization☆23Updated 5 years ago
- A simple implementation of the WaveNet model for time series forecasting☆26Updated 7 years ago
- An encoder-decoder framework for learning from incomplete data☆46Updated last year
- ☆30Updated 2 years ago
- Asymmetric Transfer Learning with Deep Gaussian Processes☆18Updated 9 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper☆51Updated 6 years ago
- Experiments with beta-VAE to learn disentangled representations from the data☆65Updated 6 years ago
- Sampled Quasi-Newton Methods for Deep Learning☆21Updated 4 years ago
- ☆28Updated 6 years ago
- Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)☆58Updated last year
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 10 months ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- The code of the paper 'Deep Forecast : Deep Learning-based Spatio-Temporal Forecasting", ICML Time Series Workshop 2017.☆119Updated 5 years ago
- Code for the PIDForest algorithm for anomaly detection☆28Updated 5 years ago
- implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)☆93Updated last month
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago