baumgach / tue-slurm-helloworld
Instructions and examples to deploy some PyTorch code on slurm using a Singularity Container
☆33Updated last year
Alternatives and similar repositories for tue-slurm-helloworld:
Users that are interested in tue-slurm-helloworld are comparing it to the libraries listed below
- Sketched matrix decompositions for PyTorch☆69Updated 3 weeks ago
- Algorithms for computations on random manifolds made easier☆87Updated last year
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆31Updated this week
- Agustinus' very opiniated publication-ready plotting library☆61Updated 2 weeks ago
- A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"☆18Updated 5 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆77Updated 3 years ago
- ☆50Updated 3 weeks ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated last year
- IVON optimizer for neural networks based on variational learning.☆59Updated 3 months ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- ☆53Updated 6 months ago
- Code for the paper "Contrastive Learning Inverts the Data Generating Process".☆90Updated 6 months ago
- Code for our paper: Online Variational Filtering and Parameter Learning☆18Updated 3 years ago
- Normalizing Flows using JAX☆82Updated last year
- ☆18Updated last year
- A Machine Learning workflow for Slurm.☆149Updated 4 years ago
- ☆32Updated 2 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆41Updated last year
- Bayesian active learning with EPIG data acquisition☆28Updated 2 weeks ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- ☆36Updated 2 years ago
- Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend☆58Updated 8 months ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆33Updated 3 years ago
- Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)☆83Updated 2 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆72Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight https://openreview.net/forum?id=XJk19XzGq2J☆65Updated 10 months ago
- Squared Non-monotonic Probabilistic Circuits☆21Updated last month
- Likelihood-free AMortized Posterior Estimation with PyTorch☆122Updated 5 months ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 4 years ago