gbaydin / oxford-poster
LaTeX beamer poster template themed for the University of Oxford
☆68Updated 2 years ago
Alternatives and similar repositories for oxford-poster:
Users that are interested in oxford-poster are comparing it to the libraries listed below
- ☆18Updated this week
- Efficient, lightweight variational inference and approximation bounds☆43Updated last year
- Differentiable and numerically stable implementation of the matrix exponential☆33Updated 4 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- ☆64Updated last year
- A Machine Learning workflow for Slurm.☆149Updated 4 years ago
- [NeurIPS'19] Deep Equilibrium Models Jax Implementation☆39Updated 4 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Pulls papers from arXiv on a weekly basis☆30Updated last year
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆84Updated 4 years ago
- Generate a customised list of publications for your LaTeX CV using BibTeX entries.☆99Updated 3 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Computational statistics and machine learning reading group at Imperial College London (2019-2020)☆24Updated 2 months ago
- Normalizing Flows using JAX☆83Updated last year
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆31Updated 3 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆100Updated last year
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- My Research Journal covering various topics that interest me. They're mostly scattered notes and resources.☆32Updated 2 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.☆75Updated 9 months ago
- ☆53Updated 9 months ago
- ☆36Updated 3 years ago
- ☆99Updated 3 years ago
- Automated Scalable Bayesian Inference☆131Updated 3 years ago
- IVON optimizer for neural networks based on variational learning.☆64Updated 6 months ago
- Normalizing Flows in Jax☆107Updated 4 years ago
- probabilistic programming focused on fun☆40Updated 6 months ago
- Official release of code for "Oops I Took A Gradient: Scalable Sampling for Discrete Distributions"☆54Updated last year