egstatsml / arxivsearch
Pulls papers from arXiv on a weekly basis
☆30Updated last year
Related projects ⓘ
Alternatives and complementary repositories for arxivsearch
- ☆15Updated 2 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 3 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆81Updated 5 months ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆55Updated 3 years ago
- Gaussian Processes for Sequential Data☆18Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆18Updated 5 years ago
- Monotone operator equilibrium networks☆51Updated 4 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 5 years ago
- ☆53Updated 3 months ago
- Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch☆22Updated 4 years ago
- ☆98Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆86Updated 4 years ago
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated last year
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆21Updated 2 years ago
- Code for Deep Structured Mixtures of Gaussian Processes (DSMGPs)☆10Updated 2 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 4 years ago
- Riemannian Convex Potential Maps☆68Updated last year
- Bayesian Coresets Construction with Accelerated Iterative Hard Thresholding (A-IHT).☆17Updated 3 years ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 2 years ago
- Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"☆10Updated 10 months ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆32Updated 2 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆86Updated 2 years ago
- Bayesian active learning with EPIG data acquisition☆25Updated 6 months ago
- Code for the paper Gaussian process behaviour in wide deep networks☆48Updated 6 years ago
- Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)☆18Updated 3 years ago
- A community repository for benchmarking Bayesian methods☆109Updated 2 years ago