Zhenyu-LIAO / RMT4ELMLinks
A Random Matrix Approach to Extreme Learning Machine
☆14Updated 7 years ago
Alternatives and similar repositories for RMT4ELM
Users that are interested in RMT4ELM are comparing it to the libraries listed below
Sorting:
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Code for Stochastic Hyperparameter Optimization through Hypernetworks☆23Updated 7 years ago
- Implementation of Information Dropout☆39Updated 8 years ago
- Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761☆37Updated 7 years ago
- Computing various norms/measures on over-parametrized neural networks☆50Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆105Updated 5 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆68Updated 5 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 6 years ago
- Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"☆73Updated 9 years ago
- Deprecated repository for "Deep Learning with Topological Signatures"☆36Updated 5 years ago
- Keras implementation of Deep Wasserstein Embeddings☆48Updated 7 years ago
- Code for Unbiased Implicit Variational Inference (UIVI)☆14Updated 6 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Code for Augment & Reduce, a scalable stochastic algorithm for large categorical distributions☆10Updated 7 years ago
- Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)☆14Updated 5 years ago
- ☆54Updated last year
- Lua implementation of Entropy-SGD☆82Updated 7 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- An empirical investigation of deep learning theory☆16Updated 6 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- A clean TensorFlow implementation of Concrete Dropout☆22Updated 7 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 5 years ago
- ☆26Updated 6 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆34Updated 10 years ago