twistedcubic / que-outlier-detectionLinks
[NeurIPS 2019 Spotlight] High dimensional mean estimation and outlier detection in nearly-linear time.
☆26Updated 6 years ago
Alternatives and similar repositories for que-outlier-detection
Users that are interested in que-outlier-detection are comparing it to the libraries listed below
Sorting:
- Official PyTorch code release for Implicit Gradient Transport, NeurIPS'19☆21Updated 6 years ago
- Nonparametric Score Estimators, ICML 2020☆36Updated 4 years ago
- [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling☆41Updated 2 years ago
- Implementation of Information Dropout☆39Updated 8 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆54Updated 6 years ago
- Geometric Certifications of Neural Nets☆42Updated 2 years ago
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆68Updated 6 years ago
- A pytorch implementation for the LSTM experiments in the paper: Why Gradient Clipping Accelerates Training: A Theoretical Justification f…☆46Updated 5 years ago
- Source code for ICLR 2020 paper: "Learning to Guide Random Search"☆40Updated last year
- Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)☆14Updated 5 years ago
- A clean TensorFlow implementation of Concrete Dropout☆22Updated 7 years ago
- Implementation of the Deep Frank-Wolfe Algorithm -- Pytorch☆62Updated 4 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 6 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 5 years ago
- The Limited Multi-Label Projection Layer☆59Updated last year
- Code for the paper "Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data" at ICML 2019.☆20Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- ☆30Updated 5 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- This repository is no longer maintained. Check☆81Updated 5 years ago
- [ICLR 2019] Learning Representations of Sets through Optimized Permutations☆36Updated 6 years ago
- Statistical adaptive stochastic optimization methods☆32Updated 5 years ago
- A PyTorch implementation of Conditional PixelCNNs☆27Updated 7 years ago
- ☆50Updated 5 years ago
- Repository containing code for getting statistical guarantees on properties of BNNs☆13Updated 6 years ago
- A pytorch implementation of Information Bottleneck GAN☆28Updated 6 years ago
- Code for NeurIPS 2019 paper: "Symmetry-Based Disentangled Representation Learning requires Interaction with Environments" by H. Caselles-…☆35Updated 5 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆27Updated 6 years ago
- Limitations of the Empirical Fisher Approximation☆48Updated 8 months ago
- Pytorch package for geometric softmax☆12Updated 6 years ago