AlvinWen428 / FeatureCP
The official codebase for Predictive Inference with Feature Conformal Prediction
☆31Updated last year
Related projects: ⓘ
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆61Updated 4 months ago
- Uncertainty Aware Semi-Supervised Learning on Graph Data☆39Updated 3 years ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆57Updated last year
- Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024☆25Updated 2 weeks ago
- Source code of "What Makes Graph Neural Networks Miscalibrated?" (NeurIPS 2022)☆18Updated last year
- Code for experiments to learn uncertainty☆28Updated last year
- Benchmark and analysis of 165 pretrained SSL models. Code for "Evaluating Self-Supervised Learning via Risk Decomposition".☆13Updated last year
- ☆21Updated 2 years ago
- Code for Diff-SCM paper☆88Updated last year
- Paper Reproduce for "Predictive Uncertainty Estimation via Prior Networks" by Andrey Malinin and Mark Gales.☆27Updated 4 years ago
- [NeurIPS 2023, Spotlight] Rank-N-Contrast: Learning Continuous Representations for Regression☆76Updated 6 months ago
- Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)☆20Updated last year
- Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)☆61Updated last year
- Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"☆12Updated 5 months ago
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems☆31Updated last year
- ☆18Updated 2 years ago
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆97Updated last year
- Supplementary material to reproduce "Multivariate Deep Evidential Regression"☆19Updated 2 years ago
- Experiments to reproduce results in Interventional Causal Representation Learning.☆25Updated last year
- ☆24Updated 2 months ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆35Updated 4 months ago
- Evidential Deep Learning in PyTorch☆39Updated last year
- [CLeaR23] Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning☆29Updated last year
- C-Mixup for NeurIPS 2022☆62Updated 9 months ago
- A python package providing a benchmark with various specified distribution shift patterns.☆53Updated 9 months ago
- ☆22Updated last year
- This repository contains an official implementation of LPBNN.☆39Updated last year
- Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"☆40Updated last year
- Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"☆22Updated last year
- PyTorch Implementation for Gromov-Wasserstein Autoencoders (GWAE)☆40Updated last year