invariance
There are 27 repositories under invariance topic.
greyblake/nutype
Rust newtype with guarantees 🇺🇦 🦀
chao1224/Geom3D
Geom3D: Geometric Modeling on 3D Structures, NeurIPS 2023
stanford-futuredata/equivariant-transformers
Equivariant Transformer (ET) layers are image-to-image mappings that incorporate prior knowledge on invariances with respect to continuous transformations groups (ICML 2019). Paper: https://arxiv.org/abs/1901.11399
beabevi/ESAN
Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)
lucmos/relreps
Relative representations can be leveraged to enable solving tasks regarding "latent communication": from zero-shot model stitching to latent space comparison between diverse settings.
sophiaas/spectral-universality
Official PyTorch and JAX Implementation of "Harmonics of Learning: Universal Fourier Features Emerge in Invariant Networks"
PurdueMINDS/size-invariant-GNNs
Size-Invariant Graph Representations for Graph Classification Extrapolations (ICML 2021 Long Talk)
sophiaas/bispectral-networks
Official PyTorch implementation of Bispectral Neural Networks, ICLR 2023
jiaqingxie/Theories-of-Graph-Neural-Networks
A List of Papers on Theoretical Foundations of Graph Neural Networks
Katalip/ca-stinv-cnn
Code for "Improving Stain Invariance of CNNs for Segmentation by Fusing Channel Attention and Domain-Adversarial Training"
ThijsKuipers1995/gconv
Continuous regular group convolutions for Pytorch
Weixy21/InvarianceNODE
On the forward invariance of Neural ODEs: performance guarantees for policy learning
MaksimRudnev/MIE.package
Measurement invariance explorer - R package to explore measurement invariance
chiukenny/Tests-for-Distributional-Symmetry
Non-parametric hypothesis tests for identifying distributional group symmetries from data
namratadeka/mmd-b-fair
MMD-B-Fair: Learning Fair Representations with Statistical Testing (AISTATS 2023)
atiaisaac/VICReg_TF
This a tensorflow implementation of VICReg - a self-supervised learning architecture that prevents collapse in an intuitive manner using a loss function that 1. maintains the variance of each embedding over a batch above a threshold and 2. decorrelating pairs of embeddings over a batch and attracting them to 0. Training was done using TPU on colab
facundoq/tmeasures
The Transformational Measures (TM) library allows neural network researchers to evaluate the invariance and equivariance of their models with respect to a set of transformations. Support for Pytorch (current) and Tensorflow/Keras (coming).
gtc-invariance/gtc-invariance
This repository is the official accompaniment to A General Framework for Robust G-Invariance in G-Equivariant Networks (submitted, NeurIPS 2023)
sophiaas/gtc-invariance
Official PyTorch Implementation of "A General Framework for Robust G-Invariance in G-Equivariant Networks," NeurIPS 2023
trajectory-invariants/invariants_mat
Matlab implementation of Trajectory Invariants.
mtumilowicz/java11-covariance-contravariance-invariance
Covariance, invariance, contravariance overview of collections in Java 11, vavr, guava.
davidsleonard/leiv
Linear Errors-In-Variables Estimation
lansaloltd/kingdom-animalia
Really simplified animal kingdom hierarchy
lansaloltd/type-variance
Some example of type variance in Scala
pvts/NN-Invariant-Elements
Identifying invariant elements of Neural Networks to image transformations
sophiecollard/variance
Simple examples to illustrate the differences between invariance, covariance and contravariance in Scala
AhmedTarekHasan/CovarianceAndContravarianceInDotNetCSharp
Have hard time understanding it? Let me simplify it for you.