TensorFlow implementation of "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

Overview

[TensorFlow 2] A Simple Baseline for Bayesian Uncertainty in Deep Learning: SWA-Gaussian (SWAG)

TensorFlow implementation of "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

Concept

Algorithm to utilize the SWAG [1].

Equation for the weight sampling from SWAG [1].

Results

The red color and the blue color represent the initial state and current state respectively.

Variable MNIST CIFAR10

Performance

MNIST

Method Accuracy Precision Recall F1-Score
Final Epoch 0.99230 0.99231 0.99222 0.99226
Best Loss 0.99350 0.99350 0.99338 0.99344
SWAG (S = 30) 0.99310 0.99305 0.99299 0.99302
SWAG (Last Momentum) 0.99340 0.99340 0.99330 0.99335

CIFAR10

Method Accuracy Precision Recall F1-Score
Final Epoch 0.73130 0.73349 0.73130 0.73147
Best Loss 0.73240 0.73205 0.73240 0.73099
SWAG (S = 30) 0.74100 0.74622 0.74100 0.74260
SWAG (Last Momentum) 0.73490 0.73888 0.73490 0.73561

Requirements

  • Python 3.7.6
  • Tensorflow 2.3.0
  • Numpy 1.18.15
  • whiteboxlayer 0.1.15

Reference

[1] Wesley Maddox et al. (2019). A Simple Baseline for Bayesian Uncertainty in Deep Learning. arXiv preprint arXiv:1902.02476.

Owner
YeongHyeon Park
YeongHyeon Park
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset

Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch implementation of semantic segmentation models on MIT ADE20K scene parsing da

MIT CSAIL Computer Vision 4.5k Jan 08, 2023
Fader Networks: Manipulating Images by Sliding Attributes - NIPS 2017

FaderNetworks PyTorch implementation of Fader Networks (NIPS 2017). Fader Networks can generate different realistic versions of images by modifying at

Facebook Research 753 Dec 23, 2022
StackNet is a computational, scalable and analytical Meta modelling framework

StackNet This repository contains StackNet Meta modelling methodology (and software) which is part of my work as a PhD Student in the computer science

Marios Michailidis 1.3k Dec 15, 2022
(NeurIPS 2020) Wasserstein Distances for Stereo Disparity Estimation

Wasserstein Distances for Stereo Disparity Estimation Accepted in NeurIPS 2020 as Spotlight. [Project Page] Wasserstein Distances for Stereo Disparity

Divyansh Garg 92 Dec 12, 2022
Cognition-aware Cognate Detection

Cognition-aware Cognate Detection The repository which contains our code for our EACL 2021 paper titled, "Cognition-aware Cognate Detection". This wor

Prashant K. Sharma 1 Feb 01, 2022
Code for the IJCAI 2021 paper "Structure Guided Lane Detection"

SGNet Project for the IJCAI 2021 paper "Structure Guided Lane Detection" Abstract Recently, lane detection has made great progress with the rapid deve

Jinming Su 27 Dec 08, 2022
Submission to Twitter's algorithmic bias bounty challenge

Twitter Ethics Challenge: Pixel Perfect Submission to Twitter's algorithmic bias bounty challenge, by Travis Hoppe (@metasemantic). Abstract We build

Travis Hoppe 4 Aug 19, 2022
MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.

Documentation | FAQ | Release Notes | Roadmap | MACE Model Zoo | Demo | Join Us | 中文 Mobile AI Compute Engine (or MACE for short) is a deep learning i

Xiaomi 4.7k Dec 29, 2022
Object Detection using YOLO from PyImageSearch

Object Detection using YOLO from PyImageSearch By applying object detection, you’ll not only be able to determine what is in an image, but also where

Mohamed NIANG 1 Feb 09, 2022
SFD implement with pytorch

S³FD: Single Shot Scale-invariant Face Detector A PyTorch Implementation of Single Shot Scale-invariant Face Detector Description Meanwhile train hand

Jun Li 251 Dec 22, 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
用强化学习DQN算法,训练AI模型来玩合成大西瓜游戏,提供Keras版本和PARL(paddle)版本

用强化学习玩合成大西瓜 代码地址:https://github.com/Sharpiless/play-daxigua-using-Reinforcement-Learning 用强化学习DQN算法,训练AI模型来玩合成大西瓜游戏,提供Keras版本、PARL(paddle)版本和pytorch版本

72 Dec 17, 2022
Automatic 2D-to-3D Video Conversion with CNNs

Deep3D: Automatic 2D-to-3D Video Conversion with CNNs How To Run To run this code. Please install MXNet following the official document. Deep3D requir

Eric Junyuan Xie 1.2k Dec 30, 2022
official Pytorch implementation of ICCV 2021 paper FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting.

FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting By Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu, Wenxiu

77 Dec 27, 2022
Individual Treatment Effect Estimation

CAPE Individual Treatment Effect Estimation Run CAPE python train_causal.py --loop 10 -m cape_cau -d NI --i_t 1 Run a baseline model python train_cau

S. Deng 4 Sep 02, 2022
Attention mechanism with MNIST dataset

[TensorFlow] Attention mechanism with MNIST dataset Usage $ python run.py Result Training Loss graph. Test Each figure shows input digit, attention ma

YeongHyeon Park 12 Jun 10, 2022
As-ViT: Auto-scaling Vision Transformers without Training

As-ViT: Auto-scaling Vision Transformers without Training [PDF] Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wang, Denny Zhou In ICLR 2

VITA 68 Sep 05, 2022
Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow

xRBM Library Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow Installation Using pip: pip install xrbm Examples Tut

Omid Alemi 55 Dec 29, 2022
Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase

Ranger-Deep-Learning-Optimizer Ranger - a synergistic optimizer combining RAdam (Rectified Adam) and LookAhead, and now GC (gradient centralization) i

Less Wright 1.1k Dec 21, 2022
Tackling Obstacle Tower Challenge using PPO & A2C combined with ICM.

Obstacle Tower Challenge using Deep Reinforcement Learning Unity Obstacle Tower is a challenging realistic 3D, third person perspective and procedural

Zhuoyu Feng 5 Feb 10, 2022