IlyaTrofimov / RTD
[ICML 2022] Representation Topology Divergence: A Method for Comparing Neural Network Representations
☆18Updated 2 years ago
Related projects: ⓘ
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆29Updated 2 years ago
- [NeurIPS 2021] Manifold Topology Divergence: a Framework for Comparing Data Manifolds☆14Updated 2 years ago
- Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight https://openreview.net/forum?id=XJk19XzGq2J☆63Updated 5 months ago
- Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"☆40Updated last year
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆43Updated last year
- Transformers with doubly stochastic attention☆40Updated 2 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆39Updated 10 months ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆9Updated last year
- A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).☆19Updated last week
- ☆16Updated 8 months ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆25Updated last year
- This is an official repository for "Learning topology-preserving data representations" presented at ICLR 2023 conference.☆27Updated last year
- Repository for "Generative Flow Networks as Entropy-Regularized RL" (AISTATS-2024, Oral)☆24Updated 4 months ago
- Code for the intrinsic dimensionality estimate of data representations☆75Updated 4 years ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆78Updated 2 years ago
- Pytorch implementation of "Entropic Neural Optimal Transport via Diffusion Processes" (NeurIPS 2023, oral).☆33Updated 6 months ago
- Entropic Optimal Transport Benchmark (NeurIPS 2023).☆18Updated 5 months ago
- ☆52Updated last month
- ☆30Updated 3 months ago
- Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities☆21Updated 5 months ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆31Updated 3 years ago
- PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)☆49Updated last year
- Implementation of Action Matching☆35Updated last year
- Instructions and examples to deploy some PyTorch code on slurm using a Singularity Container☆31Updated last year
- Official release of code for "Oops I Took A Gradient: Scalable Sampling for Discrete Distributions"☆50Updated last year
- ☆30Updated 2 years ago
- Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021.☆29Updated 2 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆45Updated 4 years ago
- A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"☆18Updated 5 years ago
- IVON optimizer for neural networks based on variational learning.☆45Updated last month