Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
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Updated
Dec 1, 2022 - Julia
Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1
This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper
Distributed, Online, and Outlier Resilient SLAM for Robotic Teams
Official implementation for the NeurIPS 2020 paper Neural Non-Rigid Tracking.
Оптимизация долгосрочного портфеля акций
A development environment for robust and global optimization
Robust GNSS Processing With Factor Graphs
Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
noisy labels; missing labels; semi-supervised learning; entropy; uncertainty; robustness and generalisation.
Code to train RL agents along with Adversarial distrubance agents
Software Release for "Incremental Covariance Estimation for Robust Localization"
Modeling robust optimization problems in Pyomo
Deep Neural Network architecture as a predictive optimal controller for {HVAC+Solar cell + battery} disturbance afflicted system vs classic Model Predictive Control
Blades: A simulator and benchmark for Byzantine-robust federated Learning with Attacks and Defenses Experimental Simulation
[Medical Image Analysis] Adversarial Data Augmentation with Chained Transformations (AdvChain)
The C++ implementation of Multi-H algorithm, which is a multi-plane fitting technique. If you use this work for Academic purposes, please cite Barath, D. and Matas, J. and Hajder, L., Multi-H: Efficient Recovery of Tangent Planes in Stereo Images. 27th British Machine Vision Conference, 2016
Robust optimization for power markets
Data-Driven Decision Making under Uncertainty in Matrix
Software release for "Enabling Robust State Estimation through Measurement Error Covariance Adaptation"
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