Skip to content
<title>Channels - Approximability in the GPAC :: FRELIP Discovery
Home
Search
Guides
Journals
Learning
FRELIP Discovery Search
Open Access Catalog for African Scholarship
Channels
Approximability in the GPAC
Search for more channels:
Similar Items: Approximability in the GPAC
Channel Options
View Record
Explore related channels
Quick Look
Verified Approximation Algorithms
Quick Look
On the Approximation of Kernel functions
Quick Look
On computable approximations of Landau's constant
Quick Look
Domains via approximation operators
Quick Look
Approximating Queries on Probabilistic Graphs
Quick Look
Predicate Abstraction with Under-approximation Refinement
Quick Look
Interpolant-Based Transition Relation Approximation
Quick Look
Approximate reasoning for real-time probabilistic processes
Quick Look
Approximation systems for functions in topological and in metric spaces
Quick Look
Exact and Approximate Determinization of Discounted-Sum Automata
Quick Look
Sound approximate and asymptotic probabilistic bisimulations for PCTL
Quick Look
Jackpot: Approximating Uncertainty Domains with Adversarial Manifolds
Quick Look
Deep Generative Models: Complexity, Dimensionality, and Approximation
Quick Look
Modular, Fully-abstract Compilation by Approximate Back-translation
Quick Look
Interpolating Between Choices for the Approximate Intermediate Value Theorem
Quick Look
Integrity Constraints Revisited: From Exact to Approximate Implication
Quick Look
Learning with Linear Function Approximations in Mean-Field Control
Quick Look
Approximating a Behavioural Pseudometric without Discount for Probabilistic Systems
Quick Look
On the Taylor expansion of $lambda$-terms and the groupoid structure of their rigid approximants
Quick Look
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions
Quick Look
The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise
Quick Look
Quantitative Approximation of the Probability Distribution of a Markov Process by Formal Abstractions
Quick Look
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples
Quick Look
PREMAP: A Unifying PREiMage APproximation Framework for Neural Networks
Load more items
View Record
Prev
Explore related channels
Next
