dpiras / GMM-MI

Related projects ⓘ

Alternatives and complementary repositories for GMM-MI

• VMBoehm / PAE
  Probabilistic Auto-Encoder
  ☆42Updated last year
• kimiandj / gsw
  ☆39Updated 4 years ago
• Yu-Group / adaptive-wavelets
  Adaptive, interpretable wavelets across domains (NeurIPS 2021)
  ☆71Updated 2 years ago
• chenlin9 / Gaussianization_Flows
  ☆22Updated 4 years ago
• PaulLyonel / conditionalSNF
  Code for the paper "Stochastic Normalizing Flows for Inverse Problems: a Markov Chains Viewpoint"
  ☆11Updated 2 years ago
• FrederikWarburg / LaplaceAE
  ☆32Updated 2 years ago
• chrvt / denoising-normalizing-flow
  ☆20Updated last year
• nhartland / KL-divergence-estimators
  Testing methods for estimating KL-divergence from samples.
  ☆62Updated 8 months ago
• biweidai / SINF
  Sliced Iterative Generator (SIG) & Gaussianizing Iterative Slicing (GIS)
  ☆36Updated last year
• dwromero / wavelet_networks
  Code repository of the paper "Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series, TMLR" https://arxiv.org/abs…
  ☆81Updated 10 months ago
• crowsonkb / mdmm
  The Modified Differential Multiplier Method (MDMM) for PyTorch
  ☆51Updated 3 years ago
• f-dangel / curvlinops
  scipy linear operators for the Hessian, Fisher/GGN, and more in PyTorch
  ☆18Updated this week
• yuyang-shi / generalized-diffusion
  ☆16Updated last year
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆30Updated 2 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 4 years ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• shagunuppal / Riemannian_Geometry_of_Deep_Generative_Models
  This repository represents a basic implementation of the paper "Riemannian Geometry of Deep Generative Models", along with the results on…
  ☆12Updated 5 years ago
• ronaldiscool / VAETutorial
  ☆17Updated 4 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 4 years ago
• locuslab / orthogonal-convolutions
  Implementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness
  ☆42Updated 3 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆71Updated 2 years ago
• J-zin / energy-discrepancy
  NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
  ☆13Updated last month
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆90Updated 7 months ago
• ganguli-lab / degrees-of-freedom
  ☆36Updated 2 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆55Updated 3 years ago
• AKuzina / attack_vae
  Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks
  ☆13Updated 2 years ago
• mwalmsley / galaxy-zoo-bayesian-cnn
  Use Bayesian CNN and Active Learning to Scale Galaxy Zoo (public)
  ☆19Updated 5 years ago
• jfcrenshaw / pzflow
  Probabilistic modeling of tabular data with normalizing flows.
  ☆55Updated 5 months ago
• aliutkus / swf
  ☆15Updated 4 years ago
• adityashrm21 / information-theory-deep-learning
  Resources and Implementations (PyTorch) for Information Theoretical concepts in Deep Learning
  ☆41Updated 5 years ago