Skip to content
pyDVL
Torch
Initializing search
aai-institute/pyDVL
Home
Getting Started
Data Valuation
The Influence Function
Examples
Code
pyDVL
aai-institute/pyDVL
Home
Getting Started
Getting Started
First steps
Applications
Benchmarking
Methods
Advanced usage
Glossary
Data Valuation
Data Valuation
Shapley values
Semi-values
The Core
Class-wise Shapley
The Influence Function
The Influence Function
Influence Function Model
Scaling Computation
Examples
Examples
Data Valuation
Data Valuation
Shapley values
KNN Shapley
Data utility learning
Least Core
Data OOB
Banzhaf Semivalues
Influence Function
Influence Function
For CNNs
For mislabeled data
For outlier detection
For language models
Code
Code
API Reference
API Reference
Influence
Influence
Array
Base influence function model
Influence calculator
Types
Torch
Torch
Base
Batch operation
Functional
Influence function model
Operator
Preconditioner
Util
Parallel
Parallel
Backend
Config
Map reduce
Backends
Backends
Joblib
Ray
Futures
Futures
Ray
Reporting
Reporting
Plots
Scores
Utils
Utils
Config
Dataset
Exceptions
Functional
Numeric
Progress
Score
Status
Types
Utility
Caching
Caching
Base
Config
Disk
Memcached
Memory
Valuation
Valuation
Base
Dataset
Games
Result
Stopping
Types
Utils
Methods
Methods
solve least core problems
utility values and sample masks
Beta shapley
Classwise shapley
Data banzhaf
Data oob
Data shapley
Delta shapley
Gt shapley
Knn shapley
Least core
Loo
Msr banzhaf
Naive
Owen shapley
Semivalue
Twodshapley
Samplers
Samplers
Base
Classwise
Msr
Permutation
Powerset
Truncation
Utils
Scorers
Scorers
Base
Classwise
Knn
Supervised
Utils
Utility
Utility
Base
Classwise
Knn
Learning
Modelutility
Value
Value
Games
Result
Sampler
Semivalues
Stopping
Least core
Least core
Common
Montecarlo
Naive
Loo
Loo
Loo
Oob
Oob
Oob
Shapley
Shapley
Classwise
Common
Gt
Knn
Montecarlo
Naive
Owen
Truncated
Types
Changelog
Development Guidelines
pydvl.influence.torch
¶
Back to top