173 Open source projects that are alternatives of or similar to uncertainty-wizard

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.

A library for uncertainty quantification based on PyTorch

(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.

A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.

Model data as beliefs (at a certain time) about events (at a certain time).

Process global-scale satellite and airborne elevation data into time series of glacier mass change: Hugonnet et al. (2021).

A developing recommender system in tensorflow2. Algorithm: UserCF, ItemCF, LFM, SLIM, GMF, MLP, NeuMF, FM, DeepFM, MKR, RippleNet, KGCN and so on.

Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)

Reusable, Easy-to-use Uncertainty module package built with Tensorflow, Keras

Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks

[ICCV 2021 Oral] Deep Evidential Action Recognition

noisy labels; missing labels; semi-supervised learning; entropy; uncertainty; robustness and generalisation.

Bayesian tools for fitting molecular mechanics torsion parameters to quantum chemical data.

Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, calibration, etc

Analysis of digital elevation models (DEMs)

Deep learning AI, that recognizes when are people uncertain

Deep learning models for guitar amp/pedal emulation using LSTM with Keras.

Keras MNIST for Handwriting Detection

Distributed Keras Engine, Make Keras faster with only one line of code.

Survival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of survival models using both a frequentist approach (by calling the R package flexsurv) and a Bayesian perspective.

C3D for Keras + TensorFlow

This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.

Artificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)

Deep neural network to extract intelligent information from invoice documents.

rstudio::conf(2020) deep learning workshop

A random forest

[ICCV'19] Calibration Wizard: A Guidance System for Camera Calibration Based on Modelling Geometric and Corner Uncertainty

Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification

Kervolution implementation using TF2.0

High-performance framework for uncertainty quantification, optimization and reinforcement learning.

[CVPR'21] MonoRUn: Monocular 3D Object Detection by Reconstruction and Uncertainty Propagation

Using neural network to build expressive hierarchical distribution; A variational method to accurately estimate posterior uncertainty; A fast and general method for Bayesian inference. (ICML 2018)

OpenCossan is an open and free toolbox for uncertainty quantification and management.

lock mechanism with face recognition and liveness detection

Fast uncertainty quantification for scientific machine learning (SciML) and differential equations

A High Level Python Library to empower students, developers to build applications and systems enabled with computer vision capabilities.

Satellite Imagery Feature Detection with SpaceNet dataset using deep UNet

Sampling nuclear data and uncertainty

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network implemented in Keras

Lightweight CRNN for OCR (including handwritten text) with depthwise separable convolutions and spatial transformer module [keras+tf]

Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray

Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020

InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy

该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。

I am taking up the #100DaysOfMLCode Challenge 😎

Implementation of Very Deep Convolutional Neural Network for Text Classification

Uncertainty-aware principal component analysis.

Some State-of-the-Art few shot learning algorithms in tensorflow 2

A collection of Wells/Drilling Engineering tools, focused on well trajectory planning for the time being.

BERT, AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Tensorflow, Mathematics

Detect Covid-19 with Chest X-Ray Data

Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.

tools for scalable and non-intrusive parameter estimation, uncertainty analysis and sensitivity analysis

Implementation of a Neural Network that can detect whether a video is in-game or not

Keras model and tensorflow optimization of 'improved Training of Wasserstein GANs'

TF2 Deep FloorPlan Recognition using a Multi-task Network with Room-boundary-Guided Attention. Enable tensorboard, quantization, flask, tflite, docker, github actions and google colab.

BioSTEAM's Premier Repository for Biorefinery Models and Results