ganguli-lab / deepchaosLinks
Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"
☆71Updated 9 years ago
Alternatives and similar repositories for deepchaos
Users that are interested in deepchaos are comparing it to the libraries listed below
Sorting:
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 6 years ago
- Lua implementation of Entropy-SGD☆82Updated 7 years ago
- paper lists and information on mean-field theory of deep learning☆78Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- ☆36Updated 4 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 6 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Lagrangian VAE☆28Updated 6 years ago
- ☆37Updated 6 years ago
- ☆169Updated 11 months ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- Graduate topics course on learning discrete latent structure.☆67Updated 6 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 6 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆66Updated 5 years ago
- Autoregressive Energy Machines☆78Updated 2 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 4 months ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- A Python implementation of the gradient REBAR estimator.☆46Updated 7 years ago
- Convolutional Neural Tangent Kernel☆111Updated 5 years ago
- ☆40Updated 6 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago