Junghwan-brian / SDE-Net
implementations sde-net
☆14Updated 4 years ago
Alternatives and similar repositories for SDE-Net
Users that are interested in SDE-Net are comparing it to the libraries listed below
Sorting:
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Training quantile models☆43Updated 5 months ago
- [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…☆14Updated 2 years ago
- PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularl…☆25Updated last year
- ☆15Updated 2 years ago
- Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"☆38Updated 2 years ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆18Updated 2 years ago
- Pytorch implementation of neural processes and variants☆29Updated 9 months ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆114Updated 4 years ago
- Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch☆22Updated 5 years ago
- PyTorch implementation of Probabilistic Network Ensembles on toy problems☆23Updated 2 years ago
- Code used for the AAAI 2020 paper "System Identification with Time-Aware Neural Sequence Models"☆17Updated 5 years ago
- Example code of Sparse Gaussian Process Attention (ICLR 2023)☆24Updated 10 months ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 4 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 3 years ago
- Accompanying code for our NeurIPS 2019 paper☆12Updated 5 years ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆17Updated 2 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- ☆16Updated 2 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆16Updated 2 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 3 years ago
- Bayesian Attention Modules☆35Updated 4 years ago
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 5 years ago
- Bayesian active learning with EPIG data acquisition☆31Updated 3 weeks ago
- Code for the paper 'Continual Learning via Sequential Function-Space Variational Inference'☆24Updated 2 years ago