mourga / variational-lstmLinks
PyTorch implementation of Variational LSTM and Monte Carlo dropout.
☆56Updated 3 years ago
Alternatives and similar repositories for variational-lstm
Users that are interested in variational-lstm are comparing it to the libraries listed below
Sorting:
- pytorch implementation of "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks" LSTM(https://arxiv.org/abs/1512.…☆21Updated 5 years ago
- Code for evaluating uncertainty estimation methods for Transformer-based architectures in natural language understanding tasks.☆43Updated 4 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
- A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]☆59Updated last year
- Transformer-based autoregressive varitional autoencoder☆11Updated 5 years ago
- Simple reimplementation of Maximum Density Divergence for Unsupervised Domain Adaptation (https://arxiv.org/abs/2004.12615) in PyTorch Li…☆26Updated 4 years ago
- How certain is your transformer?☆25Updated 4 years ago
- Official Code for Towards Transparent and Explainable Attention Models paper (ACL 2020)☆35Updated 3 years ago
- Code for the paper "A Stable Variational Autoencoder for Text Modelling"☆26Updated 5 years ago
- Mixture density network implemented in PyTorch.☆152Updated 2 years ago
- Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning☆166Updated last year
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆44Updated last year
- Pytorch implementation of "Exploring Interpretable LSTM Neural Networks over Multi-Variable Data" https://arxiv.org/pdf/1905.12034.pdf☆109Updated 6 years ago
- This is reimplementation of "Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness" in Pyt…☆52Updated 4 years ago
- Code for the EMNLP 2021 Paper "Active Learning by Acquiring Contrastive Examples" & the ACL 2022 Paper "On the Importance of Effectively …☆128Updated 3 years ago
- Contrastive Learning for Time Series☆40Updated 2 years ago
- Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)☆61Updated 2 years ago
- ☆23Updated 3 years ago
- A library for making Transformer Variational Autoencoders. (Extends the Huggingface/transformers library.)☆144Updated 4 years ago
- MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space☆41Updated 4 years ago
- Bayesian Attention Modules☆36Updated 5 years ago
- EMNLP 2020: On the Ability and Limitations of Transformers to Recognize Formal Languages☆24Updated 5 years ago
- implementation of different Dirichlet Variational Autoencoder Topic Models in Tensorflow☆49Updated 2 years ago
- Truth-Conditional Captions for Time Series Data. EMNLP 2021. Harsh Jhamtani, Taylor Berg-Kirkpatrick☆12Updated 3 years ago
- ☆91Updated 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
- ☆24Updated 5 years ago
- This is the official source code for Sequential Neural Processes.☆40Updated 3 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆63Updated 5 years ago
- Official PyTorch (Lightning) implementation of the NeurIPS 2020 paper "Efficient Marginalization of Discrete and Structured Latent Variab…☆27Updated 4 years ago