xbresson / IPAM_Tutorial_2019

Related projects: ⓘ

• convnets-as-gps / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆15Updated 5 years ago
• CalculatedContent / ImplicitSelfRegularization
  Repo to accompany paper "Implicit Self-Regularization in Deep Neural Networks..."
  ☆40Updated 5 years ago
• thegregyang / NNspectra
  Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
  ☆47Updated 5 years ago
• lzzcd001 / ade-code
  Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)
  ☆13Updated 4 years ago
• YingzhenLi / SteinGrad
  Code release for the ICLR paper
  ☆20Updated 6 years ago
• QUVA-Lab / COMBO
  ☆45Updated last month
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 6 years ago
• geomstats / applications
  Examples of more involved applications using Geomstats
  ☆32Updated 3 years ago
• ermongroup / higher_order_invariance
  Code for "Accelerating Natural Gradient with Higher-Order Invariance"
  ☆29Updated 5 years ago
• g-benton / hessian-eff-dim
  Public Codebase for Rethinking Parameter Counting: Effective Dimensionality Revisited
  ☆35Updated last year
• conormdurkan / autoregressive-energy-machines
  Autoregressive Energy Machines
  ☆77Updated last year
• 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
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 5 years ago
• random-matrix-learning / slides
  LaTeX source code for the slides
  ☆21Updated 3 years ago
• franrruiz / uivi
  Code for Unbiased Implicit Variational Inference (UIVI)
  ☆13Updated 5 years ago
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 4 years ago
• AVMCMC / AuxiliaryVariationalMCMC
  Code required to reproduce the experiments in Auxiliary Variational MCMC
  ☆17Updated 5 years ago
• AllanYangZhou / metalearning-symmetries
  Experiments for Meta-Learning Symmetries by Reparameterization
  ☆55Updated 3 years ago
• gebob19 / introduction_to_normalizing_flows
  Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'
  ☆25Updated 3 years ago
• henripal / sgld
  ☆58Updated 5 years ago
• LuisArmandoPerez / DiffusionVAE
  ☆29Updated 2 years ago
• larsmaaloee / BIVA
  BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling
  ☆29Updated 4 years ago
• AdamCobb / LCBNN
  ☆25Updated 2 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆45Updated 4 years ago
• lixilinx / psgd_tf
  Tensorflow implementation of preconditioned stochastic gradient descent
  ☆34Updated 9 months ago
• KarenUllrich / binary-VAE
  A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.
  ☆21Updated 4 years ago
• KordingLab / hilbert-constrained-gradient-descent
  Pytorch optimizers implementing Hilbert Constrained Gradient Descent
  ☆18Updated 5 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆51Updated 4 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 3 years ago
• stanfordmlgroup / disentanglement
  Official repository for our ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology
  ☆36Updated 3 years ago