nec-research / st_tauLinks
This repository contains code for the paper "Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs" (Wang, Lawrence & Niepert, ICLR 2021).
☆17Updated 4 years ago
Alternatives and similar repositories for st_tau
Users that are interested in st_tau are comparing it to the libraries listed below
Sorting:
- ☆62Updated 3 years ago
- LP-SparseMAP: Differentiable sparse structured prediction in coarse factor graphs☆41Updated 2 years ago
- Code for gradient rollback, which explains predictions of neural matrix factorization models, as for example used for knowledge base comp…☆21Updated 4 years ago
- Measuring if attention is explanation with ROAR☆22Updated 2 years ago
- Code for "Rissanen Data Analysis: Examining Dataset Characteristics via Description Length" by Ethan Perez, Douwe Kiela, and Kyungyhun Ch…☆36Updated 4 years ago
- This is a repository with the code for the EMNLP 2020 paper "Information-Theoretic Probing with Minimum Description Length"☆71Updated last year
- This repository contains the code for running the character-level Sandwich Transformers from our ACL 2020 paper on Improving Transformer …☆57Updated 5 years ago
- Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling☆30Updated 4 years ago
- Code and data for the paper "Disentangling Uncertainty in Machine Translation Evaluation", accepted at EMNLP 2022.☆23Updated 2 years ago
- Gromov-Wasserstein Alignment of Embeddings☆68Updated 4 years ago
- PyTorch code for the EMNLP 2020 paper "Embedding Words in Non-Vector Space with Unsupervised Graph Learning"☆41Updated 4 years ago
- Code for "Finetuning Pretrained Transformers into Variational Autoencoders"☆40Updated 3 years ago
- EMNLP 2021 - Frustratingly Simple Pretraining Alternatives to Masked Language Modeling☆34Updated 4 years ago
- The official repository for our paper "The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers". We s…☆67Updated 3 years ago
- Train poincare embedding using gensim☆20Updated 7 years ago
- diagNNose is a Python library that facilitates a broad set of tools for analysing hidden activations of neural models.☆82Updated 2 years ago
- Rationales for Sequential Predictions☆40Updated 3 years ago
- This is the official implementation for the paper "Learning to Scaffold: Optimizing Model Explanations for Teaching"☆19Updated 3 years ago
- ☆30Updated 3 years ago
- Code for the paper "A Fully Hyperbolic Neural Model for Hierarchical Multi-class Classification"☆17Updated 5 years ago
- Checking the interpretability of attention on text classification models☆49Updated 6 years ago
- Implementation of experiments in paper "Learning from Rules Generalizing Labeled Exemplars" to appear in ICLR2020 (https://openreview.net…☆50Updated 2 years ago
- A Pytorch implementation of the optimal transport kernel embedding☆119Updated 4 years ago
- Pytorch implementation of DiffMask☆58Updated 2 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆63Updated 5 years ago
- How certain is your transformer?☆25Updated 4 years ago
- Official Code Repo for the Paper: "How does This Interaction Affect Me? Interpretable Attribution for Feature Interactions", In NeurIPS 2…☆42Updated 3 years ago
- ☆22Updated 4 years ago
- Interpretable Neural Predictions with Differentiable Binary Variables☆85Updated 4 years ago
- Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data☆57Updated 4 years ago