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Steps in reasoning
Inferences are steps in logical reasoning, moving from premises to logical consequences. Inference is traditionally divided into deduction and induction
Inference
Process of using data analysis for predicting population data from sample data
Statistical inference is the process of using data analysis to infer properties of an underlying probability distribution. Inferential statistical analysis
Statistical_inference
Method of statistical inference
Bayesian inference (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is a method of statistical inference in which Bayes' theorem is used to calculate a probability
Bayesian_inference
Study of correct reasoning
formal and informal logic. Formal logic is the study of deductively valid inferences or logical truths. It examines how conclusions follow from premises based
Logic
Component of artificial intelligence systems
In the field of artificial intelligence, an inference engine is a software component of an intelligent system that applies logical rules to the knowledge
Inference_engine
Branch of statistics
system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable
Causal_inference
Automatic detection of the type of an expression in a formal language
In type theory, type inference (sometimes called type reconstruction) is the automatic detection of the type of an expression. These include programming
Type_inference
Execution of machine learning models on edge devices
Edge inference is the process of running machine learning or deep learning models on local devices (edge devices) such as smartphones, IoT devices, embedded
Edge_inference
Method of deriving conclusions
Rules of inference are ways of deriving conclusions from premises. They are integral parts of formal logic, serving as the logical structure of valid
Rule_of_inference
Form of reasoning
Deductive reasoning is the process of drawing valid inferences. An inference is valid if its conclusion follows logically from its premises, meaning that
Deductive_reasoning
Principle of common law
Adverse inference is a legal inference, adverse to the concerned party, drawn from silence or absence of requested evidence. It is part of evidence codes
Adverse_inference
Approximate inference methods make it possible to learn realistic models from big data by trading off computation time for accuracy, when exact learning
Approximate_inference
In mathematical logic, deep inference names a general idea in structural proof theory that breaks with the classical sequent calculus by generalising
Deep_inference
Philosophy of science concept emphasizing the need for alternative hypotheses
In philosophy of science, strong inference is a model of scientific inquiry that emphasizes the need for alternative hypotheses, rather than a single
Strong_inference
Inference seeking the simplest and most likely explanation
Abductive reasoning (also called abduction, abductive inference, or retroduction) is a form of logical inference that seeks the simplest and most likely conclusion
Abductive_reasoning
Method for estimating the parameters of economic models
Indirect inference is a simulation-based method for estimating the parameters of economic models. It is a computational method for determining acceptable
Indirect_inference
Type of statistical inference
Frequentist inference is a type of statistical inference based in frequentist probability, which treats "probability" in equivalent terms to "frequency"
Frequentist_inference
Method of logical reasoning
prediction, statistical syllogism, argument from analogy, and causal inference. There are also differences in how their results are regarded. A generalization
Inductive_reasoning
Data mining technique
An inference attack is a data mining technique performed by analyzing data in order to illegitimately gain knowledge about a subject or database. A subject's
Inference_attack
Software platform for running artificial intelligence models locally
LM Studio is large language model inference software for running and using large language models locally on personal computers. It provides tools for
LM_Studio
Computational technique
Trajectory inference or pseudotemporal ordering is a computational technique used in single-cell transcriptomics to determine the pattern of a dynamic
Trajectory_inference
Hypothesis in neuroscience
model evidence. This casts perception as Bayesian inference and action-perception cycles as active inference, where sensory feedback refines prediction-guided
Free_energy_principle
One of a number of different types of statistical inference
Fiducial inference is one of a number of different types of statistical inference. These are rules, intended for general application, by which conclusions
Fiducial_inference
Involuntary aspect of visual perception
In perceptual psychology, unconscious inference (German: unbewusster Schluss), also referred to as unconscious conclusion, is a term coined in 1867 by
Unconscious_inference
Inference engine in an expert system
reasoning) is one of the two main methods of reasoning when using an inference engine and can be described logically as repeated application of modus
Forward_chaining
Process in logic
In logic, inference is the process of deriving logical conclusions from premises known or assumed to be true. In checking a logical inference for formal
Material_inference
Treatment for OCD
Inference-based therapy (IBT), also known as inference-based cognitive behavioral therapy (I-CBT), originated as a form of cognitive therapy developed
Inference-based_therapy
Spontaneous trait inference is the term utilised in social psychology to describe the mechanism that causes individuals to form impressions of people
Spontaneous_trait_inference
Logical inference from a single statement
An immediate inference is an inference which can be made from only one statement or proposition. For instance, from the statement "All toads are green"
Immediate_inference
Methods of finding hidden information
A membership inference attack (MIA) is a privacy attack that infers whether a record was included in the set of data used to produce a given output, such
Membership_inference_attack
Artificial intelligence software company
Inference Corporation was an American software company that specialized in artificial intelligence systems. Los Angeles-based Inference was founded in
Inference_Corporation
Open-source software library for LLM inference
llama.cpp is an open-source software library that performs inference on various large language models such as Meta's Llama model. It is co-developed alongside
Llama.cpp
Statistical interpretation with many tests
rate (FWER). The larger the number of inferences made in a series of tests, the more likely erroneous inferences become. Several statistical techniques
Multiple_comparisons_problem
Uncertain inference was first described by C. J. van Rijsbergen as a way to formally define a query and document relationship in Information retrieval
Uncertain_inference
Process of logical induction or deduction during reading
Text inferencing describes the tacit or active process of logical induction or deduction during reading. Inferences are used to bridge current text ideas
Text_inferencing
Intelligent design book by William A. Dembski and Winston Ewert
The Design Inference: Eliminating Chance through Small Probabilities is a book which sets out to establish approaches by which evidence of intelligent
The_Design_Inference
Method of forming inferences
reasoning) is an inference method described colloquially as working backward from the goal. It is used in automated theorem provers, inference engines, proof
Backward_chaining
Aspect of cognitive therapy
Arbitrary inference is a classic tenet of cognitive therapy created by Aaron T. Beck in 1979. He defines the act of making an arbitrary inference as the
Arbitrary_inference
Theory and paradigm of statistics
the event or conditions related to the event. For example, in Bayesian inference, Bayes' theorem can be used to estimate the parameters of a probability
Bayesian_statistics
Phenomenon in natural language
games. You can watch a movie or you can play video games. Free choice inferences are a major topic of research in formal semantics and philosophical logic
Free_choice_inference
Type of artificial neural network
An adaptive neuro-fuzzy inference system or adaptive network-based fuzzy inference system (ANFIS) is a kind of artificial neural network that is based
Adaptive neuro fuzzy inference system
Adaptive_neuro_fuzzy_inference_system
Misuse of data analysis
correction, more sophisticated selective inference methods are available. The most common selective inference method is the use of Benjamini and Hochberg's
Data_dredging
Monograph
Geometric and Topological Inference is a monograph in computational geometry, computational topology, geometry processing, and topological data analysis
Geometric and Topological Inference
Geometric_and_Topological_Inference
2000 book by Judea Pearl
Causality: Models, Reasoning, and Inference (2000; updated 2009) is a book by Judea Pearl. It is an exposition and analysis of causality. It is considered
Causality_(book)
Formal fallacy in statistical interpretation
ecological inference fallacy or population fallacy) is a formal fallacy in the interpretation of statistical data that occurs when inferences about the
Ecological_fallacy
Rewriting system and type of formal grammar
represents a significant advancement in L-system inference, introducing the Plant Model Inference Tools (PMIT) suite. Despite the name, this tool is
L-system
Computer privacy attack
Keystroke inference attacks are a class of privacy-invasive technique that allows attackers to infer what a user is typing on a keyboard. The origins
Keystroke_inference_attack
Software able to infer logical consequences
reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by
Semantic_reasoner
Range to estimate an unknown parameter
In frequentist inference, a confidence interval (CI) determines lower and upper bounds likely to contain (in repeated sampling) the true value of an unknown
Confidence_interval
Unit of information
Cross-sectional study Natural experiment Quasi-experiment Statistical inference Statistical theory Population Statistic Probability distribution Sampling
Data
Mathematical rule for inverting probabilities
of Bayes' theorem's many applications is Bayesian inference, an approach to statistical inference, where it is used to invert the probability of observations
Bayes'_theorem
Machine-learning process
Grammar induction (or grammatical inference) is the process in machine learning of learning a formal grammar (usually as a collection of re-write rules
Grammar_induction
This is a list of rules of inference, logical laws that relate to mathematical formulae. Rules of inference are syntactical transform rules which one can
List_of_rules_of_inference
Information conveyed verbally yet not literally
many other researchers. Entailment, or implication, in logic Free choice inference Indirect speech act Presupposition Davis (2019, section 14) Grice (1975:24–26)
Implicature
Method of statistical inference
A statistical hypothesis test is a method of statistical inference used to decide whether the data provides sufficient evidence to reject a particular
Statistical_hypothesis_test
Intelligence in machines
of inference, in which a problem is solved by proving a contradiction from premises that include the negation of the problem to be solved. Inference in
Artificial_intelligence
Method of statistical analysis
dilemma is the "fundamental problem of causal inference." Because of the fundamental problem of causal inference, unit-level causal effects cannot be directly
Rubin_causal_model
Evidence indirectly supporting conclusion
Circumstantial evidence is evidence that relies on an inference to connect it to a conclusion of fact, such as a fingerprint at the scene of a crime.
Circumstantial_evidence
Archaeological theory framework
of inference is an archaeological argument outlined by Christopher Hawkes in a 1954 paper that describes increasing difficulty of making inferences about
Hawkes'_ladder_of_inference
Statistical method for molecular phylogenetics
Bayesian inference of phylogeny combines the information in the prior and in the data likelihood to create the so-called posterior probability of trees
Bayesian inference in phylogeny
Bayesian_inference_in_phylogeny
Method of estimating the parameters of a statistical model, given observations
flexible, and as such the method has become a dominant means of statistical inference. If the likelihood function is differentiable, the derivative test for
Maximum_likelihood_estimation
Mathematical methods used in Bayesian inference and machine learning
techniques for approximating intractable integrals arising in Bayesian inference and machine learning. They are typically used in complex statistical models
Variational_Bayesian_methods
Canadian philosopher (1936–2023)
translated into several languages. His works include: Logic of Statistical Inference (1965) A Concise Introduction to Logic (1972) ISBN 978-0-394-31008-4 The
Ian_Hacking
Type of machine learning model
(2022). Active Inference: The Free Energy Principle in Mind, Brain, and Behavior; Chapter 4 The Generative Models of Active Inference. The MIT Press.
Large_language_model
Type of statistical analysis
Nonparametric statistics can be used for descriptive statistics or statistical inference. Nonparametric tests are often used when the assumptions of parametric
Nonparametric_statistics
Statistical law in machine learning
training cost. Some models also exhibit performance gains by scaling inference through increased test-time compute (TTC), extending neural scaling laws
Neural_scaling_law
Number measuring the chance an event occurs
computer science, game theory, and philosophy to, for example, draw inferences about the expected frequency of events. Probability theory is also used
Probability
1994 book written by Gary King, Robert Keohane, and Sidney Verba
Designing Social Inquiry: Scientific Inference in Qualitative Research (or KKV) is an influential 1994 book written by Gary King, Robert Keohane, and
Designing_Social_Inquiry
Computational method in Bayesian statistics
posterior distributions of model parameters. In all model-based statistical inference, the likelihood function is of central importance, since it expresses
Approximate Bayesian computation
Approximate_Bayesian_computation
Algorithmic inference gathers new developments in the statistical inference methods made feasible by the powerful computing devices widely available to
Algorithmic_inference
Type of inference
Biological network inference is the process of making inferences and predictions about biological networks. By using these networks to analyze patterns
Biological_network_inference
Reason arguing against a premise, argument, or conclusion; expression of disagreement
Parmenides – is commonly referred to as a retroactive refutation. An inference objection is an objection to an argument based not on any of its stated
Objection_(argument)
2011 Japanese novel by Kyo Shirodaira and its adaptations
In/Spectre (Japanese: 虚構推理, Hepburn: Kyokō Suiri), also known as Invented Inference in Japan, is a 2011 Japanese novel published by Kodansha and written by
In/Spectre
Study of collection and analysis of data
specific experiment designs and survey samples. Random sampling assures that inferences and conclusions can reasonably extend from the sample to the population
Statistics
Method of deduction
the statement "if it is raining then it is cloudy." The only logical inference that one can draw from this is that "if it is not cloudy then it is not
Plausible_reasoning
System for reasoning about vagueness
usually used within other complex methods, such as in adaptive neuro fuzzy inference systems. Since the fuzzy system output is a consensus of all of the inputs
Fuzzy_logic
American multinational technology company
deal included a non-exclusive licensing agreement with Nvidia for Groq's inference technology. Several of Groq's senior leaders, including its CEO, also
Nvidia
Inference method in biological sciences
Phylogenetic bracketing is a method of inference used in biological sciences. It is used to infer the likelihood of unknown traits in organisms based
Phylogenetic_bracketing
Memory allocation scheme
regions for safe memory allocation by introducing the concept of region inference, where the creation and deallocation of regions, as well as the assignment
Region-based memory management
Region-based_memory_management
Set of random variables
likelihood of a model requires inference in the model, which is generally computationally infeasible (see 'Inference' below). A multivariate normal distribution
Markov_random_field
Mathematical theory
Solomonoff's theory of inductive inference in philosophy is a method of evaluating scientific models according to their description length. According
Solomonoff's theory of inductive inference
Solomonoff's_theory_of_inductive_inference
Domesticated species of canid
to solve problems. Studies of two dogs suggest that dogs can learn by inference. A study with Rico, a Border Collie, showed that he knew the labels of
Dog
Philosophical problem-solving principle
known entities for inferences to unknown entities." Around 1960, Ray Solomonoff founded the theory of universal inductive inference, the theory of prediction
Occam's_razor
Theory and paradigm of statistics
of statistical inference, while others make inferences based on likelihood, but without using Bayesian inference or frequentist inference. Likelihoodism
Likelihoodist_statistics
In constraint satisfaction, constraint inference is a relationship between constraints and their consequences. A set of constraints D {\displaystyle D}
Constraint_inference
language model inference and fine-tuning on Apple silicon. SGLang – framework for structured generation and high-performance LLM inference and serving vLLM
Lists of open-source artificial intelligence software
Lists_of_open-source_artificial_intelligence_software
American Founding Father (died 1804)
Reviews in American History 2005, pp. 33(1):8–14, finding Chernow's inferences to be overreading the contemporary style. Katz, Jonathan Ned, Gay American
Alexander_Hamilton
System of formal deduction in logic
system that generates theorems from axioms and inference rules, especially if the only postulated inference rule is modus ponens. Every Hilbert system is
Hilbert_system
American artificial intelligence model routing platform
through which developers can access models from multiple developers and inference providers. OpenRouter claims to have 600 trillion monthly tokens and 10
OpenRouter
Social media platform owned by Meta
trial or case-control, meaning they were incapable of drawing causal inferences. The WSJ reported that Instagram can worsen poor body image of young people
Refutation of a logical fallacy
system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable
Correlation does not imply causation
Correlation_does_not_imply_causation
American technology company
also develops related computer hardware and software to accelerate AI inference performance. Examples of the types of AI workloads that run on Groq's
Groq
Artificial intelligence project
Level) modules were described in Lenat and Guha's textbook, but the Cyc inference engine code and the full list of HL modules are Cycorp-proprietary. The
Cyc
Artificial intelligence model developed by TypeSafe AI
it can perform zero-shot learning of input for categories provided at inference time, based on contextual information provided. TypeSafe describes Jev
Jev_(AI_model)
Location inference is the method of identifying the location profiles of users on social media platforms such as Twitter and Facebook from their message
Location_inference
Style of formal logical argumentation
earlier lines in a formal argument according to rules and procedures of inference, giving a better approximation to the natural style of deduction used
Sequent_calculus
Public cloud and edge provider
training, fine-tuning, and inference. In January 2025, the company introduced Everywhere Inference, a serverless inference solution that enables AI model
Gcore
Question of whether inductive reasoning leads to definitive knowledge
based on previous observations. These inferences from the observed to the unobserved are known as "inductive inferences". David Hume, who first formulated
Problem_of_induction
Checking software against expectations
specifications, contracts, comparable products, past versions of the same product, inferences about intended or expected purpose, user or customer expectations, relevant
Software_testing
Theory in psychology
major domains of deductive inference, including relational inferences (spatial and temporal reasoning), propositional inferences (conditional, disjunctive
Mental model theory of reasoning
Mental_model_theory_of_reasoning
travel, tourism, insurance
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travel, tourism, insurance