kibitzing / BayesianRNN_pytorchLinks
pytorch implementation of "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks" LSTM(https://arxiv.org/abs/1512.05287)
☆21Updated 4 years ago
Alternatives and similar repositories for BayesianRNN_pytorch
Users that are interested in BayesianRNN_pytorch are comparing it to the libraries listed below
Sorting:
- PyTorch implementation of Variational LSTM and Monte Carlo dropout.☆56Updated 3 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- Custom loss functions to use in (mainly) PyTorch.☆39Updated 4 years ago
- ☆238Updated 5 years ago
- implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)☆97Updated 5 months ago
- Pytorch implementation of "Exploring Interpretable LSTM Neural Networks over Multi-Variable Data" https://arxiv.org/pdf/1905.12034.pdf☆109Updated 5 years ago
- An encoder-decoder framework for learning from incomplete data☆45Updated 2 years ago
- Bayesian LSTM (Tensorflow)☆55Updated 2 years ago
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆205Updated 3 years ago
- TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155☆142Updated 2 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆114Updated 4 years ago
- Bayesian, Uncertainty, Neutral Networks, LSTM, time series☆40Updated 5 years ago
- An LSTM in PyTorch with best practices (weight dropout, forget bias, etc.) built-in. Fully compatible with PyTorch LSTM.☆134Updated 5 years ago
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆43Updated 9 months ago
- Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series☆118Updated 2 years ago
- This repository has implementation and tutorial for Deep Belief Network☆101Updated 6 years ago
- inspired by 'Recurrent Neural Networks for Multivariate Time Series with Missing Values' pytorch ver☆117Updated 6 years ago
- Contrastive Learning for Time Series☆40Updated 2 years ago
- Pytorch implementation of GRU-ODE-Bayes☆228Updated 3 years ago
- Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)☆59Updated 2 years ago
- PyTorch Implementation of GRU-D from "Recurrent Neural Networks for Multivariate Time Series with Missing Values" https://arxiv.org/abs/1…☆26Updated 5 years ago
- A Pytorch Implementation of Attentive Neural Process☆75Updated 6 years ago
- implementations sde-net☆14Updated 4 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆112Updated 3 years ago
- ☆19Updated 4 years ago
- A quick walk-through of the innards of LSTMs and a naive implementation of the Mogrifier LSTM paper in PyTorch☆78Updated 5 years ago
- Bayesian LSTM Implementation in PyTorch☆111Updated 2 years ago
- Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance☆76Updated 6 years ago
- Pytorch implementation of the Variational Recurrent Neural Network (VRNN).☆287Updated 3 years ago
- A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.☆52Updated 5 years ago