aradha5772 / deep_learning_theory_tutorialLinks
☆15Updated 4 years ago
Alternatives and similar repositories for deep_learning_theory_tutorial
Users that are interested in deep_learning_theory_tutorial are comparing it to the libraries listed below
Sorting:
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 5 years ago
- ☆54Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆46Updated 3 years ago
- Euclidean Wasserstein-2 optimal transportation☆46Updated 2 years ago
- Baselines for Model-Based Optimization☆55Updated 4 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆48Updated 2 years ago
- Meta-learning Gaussian process (GP) priors via PAC-Bayes bounds☆26Updated 2 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- [ICML'21] Improved Contrastive Divergence Training of Energy Based Models☆69Updated 3 years ago
- ☆37Updated 5 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 6 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 3 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆78Updated 2 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆78Updated 4 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆28Updated 4 years ago
- An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)☆42Updated 3 years ago
- Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …☆41Updated 5 years ago
- Neural Ensemble Search for Uncertainty Estimation and Dataset Shift☆33Updated 3 weeks ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆88Updated 2 years ago
- ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows☆54Updated 3 years ago
- Expressive Power of Invariant and Equivariant Graph Neural Networks (ICLR 2021)☆41Updated 2 years ago
- paper lists and information on mean-field theory of deep learning☆79Updated 6 years ago
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆17Updated 3 years ago
- Pytorch implementation of KFAC and E-KFAC (Natural Gradient).☆133Updated 6 years ago
- Codebase for Learning Invariances in Neural Networks☆96Updated 3 years ago
- Bayesian Optimization with Density-Ratio Estimation☆24Updated 3 years ago
- [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…☆14Updated 3 years ago