Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Concept
Denotational semantics
Formal sciences
Theoretical computer science
Programming language theory
Formal semantics
Graph Chatbot
Related lectures (30)
Login to filter by course
Login to filter by course
Reset
Previous
Page 3 of 3
Next
Coq Workshop: Introduction to Interactive Theorem Proving
Introduces Coq, an interactive theorem assistant based on the Curry-Howard isomorphism.
Operational Semantics: Amyli Language
Explores operational semantics and inductively defined relations in the Amyli language.
Polymorphism in Coq: Data Structures and Functions
Covers polymorphism in Coq, focusing on data structures and functions like lists, length, and append.
Big-step semantics: Defining arithmetic expressions and commands
Covers the definition of a simple programming language and its big-step semantics, including arithmetic expressions and imperative commands.
Lambda Calculus: Operational Semantics and Evaluation Strategies
Covers operational semantics and evaluation strategies in lambda calculus, including redex, alternative evaluation strategies, and Church Booleans.
Knowledge Representation: Semantics and Data Structures
Explores knowledge representation, data structures, semantics, and the challenges of searching for data on the web.
Effective Altruism: AI Safety and Governance
Covers effective altruism in AI safety, focusing on programming semantics and memory management.
Reactive Streams: Semantics & Challenges
Introduces Reactive Streams semantics, focusing on back-pressure, flow control, methods as signals, specification, challenges, and interoperability.
Simply Typed Lambda Calculus: Foundations and Properties
Covers the simply typed lambda calculus, focusing on its syntax, semantics, and type system properties such as progress and preservation.
Compositional Representations and Systematic Generalization
Examines systematicity, compositionality, neural network challenges, and unsupervised learning in NLP.