maximevictor / topo-learningLinks
Topology of Learning in Artificial Neural Networks
☆15Updated 6 years ago
Alternatives and similar repositories for topo-learning
Users that are interested in topo-learning are comparing it to the libraries listed below
Sorting:
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 7 years ago
- Repo to accompany paper "Implicit Self-Regularization in Deep Neural Networks..."☆47Updated 7 years ago
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 7 years ago
- Autoregressive Energy Machines☆78Updated 3 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- NeurIPS 2018. Linear-time model comparison tests.☆18Updated 5 years ago
- Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses☆194Updated 2 years ago
- Courses and practical sessions for the Optimal Transport and Machine learning course at Statlearn 2018☆26Updated 7 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Code for our paper "Sparse Attentive Backtracking: Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding" https://p…☆39Updated 6 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆47Updated 7 years ago
- Mixture Density Networks (Bishop, 1994) tutorial in JAX☆61Updated 5 years ago
- Variational Fourier Features☆87Updated 4 years ago
- InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy☆148Updated last year
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆184Updated 7 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆34Updated 10 years ago
- Implementation of linear CorEx and temporal CorEx.☆36Updated 4 years ago
- Original PyTorch implementation of the Leap meta-learner (https://arxiv.org/abs/1812.01054) along with code for running the Omniglot expe…☆147Updated 2 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆141Updated 9 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 9 years ago
- Summaries and minimal implementations of ML / statistics research articles.☆39Updated 4 years ago
- ☆51Updated 10 years ago
- ☆11Updated 9 years ago
- Interpreting neural networks via the STREAK algorithm (streaming weak submodular maximization)☆23Updated 8 years ago
- Loss Landscapes of Regularized Linear Autoencoders☆147Updated 3 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 7 years ago