kyg0910 / -STT997-Deep-Generative-Model
☆31Updated 3 weeks ago
Alternatives and similar repositories for -STT997-Deep-Generative-Model:
Users that are interested in -STT997-Deep-Generative-Model are comparing it to the libraries listed below
- Large-scale uncertainty benchmark in deep learning.☆56Updated 3 months ago
- Code related to different aspects of conformal learning☆16Updated 2 months ago
- "How to Trust Your Diffusion Models: A Convex Optimization Approach to Conformal Risk Control"☆17Updated last month
- Conditional calibration of conformal p-values for outlier detection.☆34Updated 2 years ago
- A package for conformal prediction with conditional guarantees.☆54Updated 2 months ago
- ☆22Updated 7 months ago
- A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…☆52Updated last year
- Lecture Notes on Statistical Inference☆76Updated 6 months ago
- SSCP: Improving Adaptive Conformal Prediction Using Self-supervised Learning (AISTATS 2023)☆17Updated 2 years ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆66Updated 2 years ago
- ☆13Updated last year
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆44Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Official repository of the paper "A Variational Approximation for Analyzing the Dynamics of Panel Data". Mixed Effect Neural ODE. UAI 202…☆8Updated 3 years ago
- Materials of the Nordic Probabilistic AI School 2023.☆91Updated last year
- ☆11Updated last year
- Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with…☆55Updated 2 years ago
- Benchmark study of quality and faithfulness of counterfactual image generation☆21Updated last month
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆169Updated 11 months ago
- Code used in the causality course (401-4632-15) at ETH Zurich.☆22Updated 5 years ago
- The Official PyTorch Implementation of "Poisson Variational Autoencoder" (NeurIPS 2024 Spotlight Paper)☆19Updated 3 weeks ago
- Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.☆17Updated last year
- Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024☆28Updated 7 months ago
- Martingale Posteriors with Copulas☆18Updated last year
- [NeurIPS 2024] Official implementation of the paper "MambaLRP: Explaining Selective State Space Sequence Models".☆38Updated 5 months ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆129Updated 2 years ago
- ☆48Updated last year
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆66Updated 5 months ago
- This repository is a curated collection of information (keywords, papers, libraries, books, etc.) about counterfactual explanations🙃 Con…☆18Updated 2 years ago