ajfisch / conformal-cascadesLinks
Efficient Conformal Prediction via Cascaded Inference with Expanded Admission
☆20Updated 4 years ago
Alternatives and similar repositories for conformal-cascades
Users that are interested in conformal-cascades are comparing it to the libraries listed below
Sorting:
- Code for paper "When Can Models Learn From Explanations? A Formal Framework for Understanding the Roles of Explanation Data"☆14Updated 4 years ago
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Updated 2 years ago
- CascadER: Cross-Modal Cascading for Knowledge Graph Link Prediction (arXiv 22)☆13Updated 3 years ago
- Measuring if attention is explanation with ROAR☆22Updated 2 years ago
- This is the official implementation for the paper "Learning to Scaffold: Optimizing Model Explanations for Teaching"☆19Updated 3 years ago
- Deep Weighted Averaging Classifiers☆23Updated 6 years ago
- Layerwise Relevance Visualization in Convolutional Text Graph Classifiers☆12Updated 4 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
- Code for Residual Energy-Based Models for Text Generation in PyTorch.☆25Updated 4 years ago
- ☆16Updated 3 years ago
- ☆13Updated 2 years ago
- This repository contains some of the code used in the paper "Training Language Models with Langauge Feedback at Scale"☆27Updated 2 years ago
- Gromov-Wasserstein Alignment of Embeddings☆66Updated 3 years ago
- This is reimplementation of "Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness" in Pyt…☆52Updated 4 years ago
- Group-conditional DRO to alleviate spurious correlations☆15Updated 4 years ago
- Checkout the new version at the link!☆22Updated 4 years ago
- This is the official PyTorch implementation of our NeurIPS 2021 paper: "SalKG: Learning From Knowledge Graph Explanations for Commonsense…☆14Updated 3 years ago
- "Predict, then Interpolate: A Simple Algorithm to Learn Stable Classifiers" ICML 2021☆18Updated 4 years ago
- CausaLM: Causal Model Explanation Through Counterfactual Language Models☆55Updated 5 years ago
- The code for the paper *The Sensitivity of Counterfactual Fairness to Unmeasured Confounding* @ UAI 2019☆12Updated 5 years ago
- Code for EMNLP 2021 paper "Measuring Association Between Labels and Free-Text Rationales"☆12Updated 2 years ago
- A lightweight implementation of removal-based explanations for ML models.☆58Updated 4 years ago
- ☆50Updated 3 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆41Updated 2 years ago
- The implementation for "Open Relation Modeling: Learning to Define Relations between Entities" (Findings of ACL '22)☆12Updated 3 years ago
- Multiple Generalized Additive Models implemented in Python (EBM, XGB, Spline, FLAM). Code for our KDD 2021 paper "How Interpretable and T…☆12Updated 4 years ago
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR☆63Updated 5 years ago
- Explaining neural decisions contrastively to alternative decisions.☆25Updated 4 years ago
- Interpretable Neural Predictions with Differentiable Binary Variables☆85Updated 4 years ago
- Code for "Using Embeddings to Correct for Unobserved Confounding"☆10Updated 6 years ago