Code related to the manuscript "Averting A Crisis In Simulation-Based Inference"

Overview

Abstract

We present extensive empirical evidence showing that current Bayesian simulation-based inference algorithms are inadequate for the falsificationist methodology of scientific inquiry. Our results collected through massive experimental computations show that all benchmarked algorithms -- (S)NPE, (S)NRE, SNL and variants of ABC -- may produce overconfident posterior approximations, which makes them demonstrably unreliable and dangerous if one's scientific goal is to constrain parameters of interest. We believe that failing to address this issue will lead to a well-founded trust crisis in simulation-based inference. For this reason, we argue that research efforts should now focus on theoretical and methodological developments of conservative approximate inference algorithms and present research directions towards this objective. In this regard, we show empirical evidence that ensembles are consistently more reliable.

A PDF render of the manuscript is available in this repo or on ArXiV.

Using the code

Recommended. This installs a Python 3 environment by default.

[email protected]:~ $ wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
[email protected]:~ $ sh Miniconda3-latest-Linux-x86_64.sh

Next, install the necessary dependencies.

[email protected]:~ conda env create -f environment.yml
[email protected]:~ conda activate crisissbi

After the environment has been activated, there are 2 ways to execute the pipelines depending on your setup. The first only requires your laptop. In that regard simply execute a pipeline as follows:

[email protected]:~ cd workflows/auc_demonstration
[email protected]:~ python pipeline.py

The other approach is on a Slurm enabled HPC cluster. To exploit the parallelism, execute the script as

[email protected]:~ cd workflows/auc_demonstration
[email protected]:~ python pipeline.py --slurm

The jobs will be automatically submitted to the default Slurm queue.

Citation

See CITATION.cff

License

Described the LICENSE file.

Owner
Montefiore Artificial Intelligence Research
Artificial Intelligence Research at the Montefiore Institute of the University of Liège.
Montefiore Artificial Intelligence Research
meProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)

meProp The codes were used for the paper meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting (ICML 2017) [pdf]

LancoPKU 107 Nov 18, 2022
AI创造营 :Metaverse启动机之重构现世,结合PaddlePaddle 和 Wechaty 创造自己的聊天机器人

paddle-wechaty-Zodiac AI创造营 :Metaverse启动机之重构现世,结合PaddlePaddle 和 Wechaty 创造自己的聊天机器人 12星座若穿越科幻剧,会拥有什么超能力呢?快来迎接你的专属超能力吧! 现在很多年轻人都喜欢看科幻剧,像是复仇者系列,里面有很多英雄、超

105 Dec 22, 2022
Public scripts, services, and configuration for running a smart home K3S network cluster

makerhouse_network Public scripts, services, and configuration for running MakerHouse's home network. This network supports: TODO features here For mo

Scott Martin 1 Jan 15, 2022
Implicit Graph Neural Networks

Implicit Graph Neural Networks This repository is the official PyTorch implementation of "Implicit Graph Neural Networks". Fangda Gu*, Heng Chang*, We

Heng Chang 48 Nov 29, 2022
Source code for "Progressive Transformers for End-to-End Sign Language Production" (ECCV 2020)

Progressive Transformers for End-to-End Sign Language Production Source code for "Progressive Transformers for End-to-End Sign Language Production" (B

58 Dec 21, 2022
Realtime Face Anti Spoofing with Face Detector based on Deep Learning using Tensorflow/Keras and OpenCV

Realtime Face Anti-Spoofing Detection 🤖 Realtime Face Anti Spoofing Detection with Face Detector to detect real and fake faces Please star this repo

Prem Kumar 86 Aug 03, 2022
The codebase for our paper "Generative Occupancy Fields for 3D Surface-Aware Image Synthesis" (NeurIPS 2021)

Generative Occupancy Fields for 3D Surface-Aware Image Synthesis (NeurIPS 2021) Project Page | Paper Xudong Xu, Xingang Pan, Dahua Lin and Bo Dai GOF

xuxudong 97 Nov 10, 2022
Classify the disease status of a plant given an image of a passion fruit

Passion Fruit Disease Detection I tried to create an accurate machine learning models capable of localizing and identifying multiple Passion Fruits in

3 Nov 09, 2021
An open source Jetson Nano baseboard and tools to design your own.

My Jetson Nano Baseboard This basic baseboard gives the user the foundation and the flexibility to design their own baseboard for the Jetson Nano. It

NVIDIA AI IOT 57 Dec 29, 2022
Mask2Former: Masked-attention Mask Transformer for Universal Image Segmentation in TensorFlow 2

Mask2Former: Masked-attention Mask Transformer for Universal Image Segmentation in TensorFlow 2 Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexan

Phan Nguyen 1 Dec 16, 2021
Run Keras models in the browser, with GPU support using WebGL

**This project is no longer active. Please check out TensorFlow.js.** The Keras.js demos still work but is no longer updated. Run Keras models in the

Leon Chen 4.9k Dec 29, 2022
Deep Structured Instance Graph for Distilling Object Detectors (ICCV 2021)

DSIG Deep Structured Instance Graph for Distilling Object Detectors Authors: Yixin Chen, Pengguang Chen, Shu Liu, Liwei Wang, Jiaya Jia. [pdf] [slide]

DV Lab 31 Nov 17, 2022
[NeurIPS'21] Shape As Points: A Differentiable Poisson Solver

Shape As Points (SAP) Paper | Project Page | Short Video (6 min) | Long Video (12 min) This repository contains the implementation of the paper: Shape

394 Dec 30, 2022
Multi-layer convolutional LSTM with Pytorch

Convolution_LSTM_pytorch Thanks for your attention. I haven't got time to maintain this repo for a long time. I recommend this repo which provides an

Zijie Zhuang 733 Dec 30, 2022
《Dual-Resolution Correspondence Network》(NeurIPS 2020)

Dual-Resolution Correspondence Network Dual-Resolution Correspondence Network, NeurIPS 2020 Dependency All dependencies are included in asset/dualrcne

Active Vision Laboratory 45 Nov 21, 2022
Adaptive Graph Convolution for Point Cloud Analysis

Adaptive Graph Convolution for Point Cloud Analysis This repository contains the implementation of AdaptConv for point cloud analysis. Adaptive Graph

64 Dec 21, 2022
Image restoration with neural networks but without learning.

Warning! The optimization may not converge on some GPUs. We've personally experienced issues on Tesla V100 and P40 GPUs. When running the code, make s

Dmitry Ulyanov 7.4k Jan 01, 2023
An AI Assistant More Than a Toolkit

tymon An AI Assistant More Than a Toolkit The reason for creating framework tymon is simple. making AI more like an assistant, helping us to complete

TymonXie 46 Oct 24, 2022
A curated list of references for MLOps

A curated list of references for MLOps

Larysa Visengeriyeva 9.3k Jan 07, 2023
Official Pytorch implementation of the paper: "Locally Shifted Attention With Early Global Integration"

Locally-Shifted-Attention-With-Early-Global-Integration Pretrained models You can download all the models from here. Training Imagenet python -m torch

Shelly Sheynin 14 Apr 15, 2022