An uncertain data having a definite value when measured.
Neural router for AI agent orchestration - FastGRNN-based intelligent routing with circuit breaker, uncertainty estimation, and hot-reload
Value-Suppressing Uncertainty Palettes. A technique for creating bivariate scales for depicting uncertainty, using D3.
A programming language for uncertainty
Uncertainty-aware principal component analysis.
Self-learning demand forecasting and swarm-based inventory optimization with uncertainty quantification
Neural router for AI agent orchestration - FastGRNN-based intelligent routing with circuit breaker, uncertainty estimation, and hot-reload
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Backstage frontend plugin for architectural hypotheses, uncertainty/impact tracking, and technical planning.
Thunk queue for uncertainty tasks evaluation.
Typed-uncertainty classification for TypeScript. Bind a domovoi to your code; receive Verdicts with calibrated probability and structured failure modes.
A module for handling physics-style uncertainty-strings, like 1.873(34)
Real-time uncertainty index from 30,000+ prediction markets. One function, one number (0-100).
DEPRECATED - Please use @prism-lang/core instead
A Redux middleware that adds uncertainty
CSL style for International Journal for Uncertainty Quantification
Estimate hallucination risk from answer, context, citations, and uncertainty language.
Official TypeScript/JavaScript SDK for Morbid AI - An Heir ecosystem project providing actuarial mortality predictions with thermal uncertainty quantification
A mathematically correct Node.js/TypeScript implementation of the Whole History Rating (WHR) algorithm with fixed prior calculations and complete uncertainty estimation
LangChain tools for prediction market data. World state, uncertainty index, edges, and market detail from 30,000+ markets.
A bunch of tools to deal with uncertainty
Official TypeScript/JavaScript SDK for Morbid AI - An Heir ecosystem project providing actuarial mortality predictions with thermal uncertainty quantification
CSL style for Journal of Risk and Uncertainty
Conformal prediction with formal verification: CPD, PCP, streaming calibration, and Lean4 proofs
Format values with PDG-style uncertainty notation.
A package for handling quantities with uncertainties.
Calculate a player's skill rating using algorithms like Elo, Glicko-2, TrueSkill and many more.
A First-Order Type for Uncertain Programming for the DeepCausality project.'
LLM-powered interpretation for 7sense bioacoustics platform
Bayesian Linear Regression with Automatic Relevance Determination for interpretable, sparse modeling in embedded and WASM environments
Orbit determination toolkit in Rust. Provides astrometric parsing, observer management, and initial orbit determination (Gauss method) with JPL ephemeris support.
DSFB-RF Structural Semiotics Engine for RF Signal Monitoring - A Deterministic, Non-Intrusive Observer Layer for Typed Structural Interpretation of IQ Residual Streams in Electronic Warfare, Spectrum Monitoring, and Cognitive Radio
Uncertainty propagation and manipulation
Natural Gradient Boosting for Probabilistic Prediction - A Rust implementation of NGBoost
A Rust library for uncertainty-aware programming, implementing the approach from 'Uncertain<T>: A First-Order Type for Uncertain Data'
Models individual differences in tolerance for ambiguity and uncertainty for brain-modeled agentic AI
holder for decision logic
A library that provides uncertainty and error propagation calculations for floats. It displays the appropriate number of digits when a number is outputted, can convert to latex using different formats.
Uses James Shore's method to calculate risk-adjusted burn-up.
Provides a Tolerance object and a Tolerances collection to facilitate specifying and analyzing variabilities and uncertainties. To aid in sampling for Monte-Carlos applications, this package also includes some inverse cummulative probability distribution functions.
'Uncertain' adds a Numeric class that encapsulates and handles numbers with uncertainty (e.g., 1.0 +/- 0.2).
Provides an easy way to round any value with a given uncertainty following PDG rounding rules. Mainly consists of a Pdground module witha round method which will round the central value and uncertainty.
there are many uncertainties about this project so I dont know:)
Chance is a little Ruby library for expressing uncertainty in your code. Maybe you always wanted to program with probability?
The Option type models the possible absence of a value. It lets us deal with the uncertainty related to such a value being there without having to resort to errors or conditional blocks.
Noisy sensor data, approximations in the equations that describe the system evolution, and external factors that are not accounted for all place limits on how well it is possible to determine the system's state. The Kalman filter deals effectively with the uncertainty due to noisy sensor data and to some extent also with random external factors. The Kalman filter produces an estimate of the state of the system as an average of the system's predicted state and of the new measurement using a weighted average. The purpose of the weights is that values with better (i.e., smaller) estimated uncertainty are "trusted" more. The weights are calculated from the covariance, a measure of the estimated uncertainty of the prediction of the system's state. The result of the weighted average is a new state estimate that lies between the predicted and measured state, and has a better estimated uncertainty than either alone. This process is repeated at every time step, with the new estimate and its covariance informing the prediction used in the following iteration. This means that the Kalman filter works recursively and requires only the last "best guess", rather than the entire history, of a system's state to calculate a new state.
The Random Sources library provides genuine random numbers, generated by processes fundamentally governed by inherent uncertainty instead of some pseudo-random number algorithm. It uses http services from different online providers.
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