IlyaTrofimov / RTDLinks
[ICML 2022] Representation Topology Divergence: A Method for Comparing Neural Network Representations
☆25Updated 3 years ago
Alternatives and similar repositories for RTD
Users that are interested in RTD are comparing it to the libraries listed below
Sorting:
- This is an official repository for "Learning topology-preserving data representations" presented at ICLR 2023 conference.☆33Updated 2 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.☆150Updated 3 years ago
- [NeurIPS 2021] Manifold Topology Divergence: a Framework for Comparing Data Manifolds☆15Updated 3 years ago
- ☆11Updated 3 years ago
- The essence of my research, distilled for reusability. Enjoy 🥃!☆69Updated last year
- Proximal Optimal Transport Modeling of Population Dynamics (AISTATS 2022)☆20Updated 2 years ago
- Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight https://openreview.net/forum?id=XJk19XzGq2J☆71Updated last year
- Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"☆11Updated last year
- ☆37Updated 5 years ago
- ☆17Updated 2 years ago
- Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)☆21Updated 2 years ago
- Code for the intrinsic dimensionality estimate of data representations☆84Updated 5 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆78Updated 4 years ago
- Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021.☆32Updated 6 months ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆37Updated 3 years ago
- PyTorch implementation of "Robust Barycenter Estimation using Semi-unbalanced Neural Optimal Transport" (ICLR 2025)☆12Updated 3 months ago
- Code for Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles [AISTATS'23]☆12Updated 2 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- Persistence differentiation with Gudhi and Tensorflow☆19Updated 2 years ago
- A Python package for intrinsic dimension estimation☆93Updated 3 weeks ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 4 months ago
- Code for Neural Manifold Clustering and Embedding☆61Updated 3 years ago
- Entropic Optimal Transport Benchmark (NeurIPS 2023).☆25Updated last year
- VAEs and nonlinear ICA: a unifying framework☆38Updated 5 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆33Updated 4 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Transformers with doubly stochastic attention☆48Updated 3 years ago
- ☆25Updated last year