cambridge-mlg / mphil-intro-moduleLinks
Jupyter notebooks on inference, regression and classification for MPhil students
☆54Updated 10 months ago
Alternatives and similar repositories for mphil-intro-module
Users that are interested in mphil-intro-module are comparing it to the libraries listed below
Sorting:
- Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille☆89Updated 6 months ago
- Materials of the Nordic Probabilistic AI School 2022.☆180Updated 2 years ago
- MPhil Machine Learning and Machine Intelligence @ University of Cambridge☆51Updated 6 years ago
- ☆243Updated 2 years ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆41Updated this week
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆108Updated last year
- Materials of the Nordic Probabilistic AI School 2023.☆90Updated last year
- IVON optimizer for neural networks based on variational learning.☆70Updated 9 months ago
- Density Ratio Estimation via Infinitesimal Classification (AISTATS 2022 Oral)☆20Updated 3 years ago
- This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…☆308Updated 2 months ago
- Laplace approximations for Deep Learning.☆515Updated 4 months ago
- A Machine Learning workflow for Slurm.☆150Updated 4 years ago
- Implementation of normalizing flows in TensorFlow 2 including a small tutorial.☆147Updated last month
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆137Updated 2 months ago
- A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…☆56Updated last year
- Simple (and cheap!) neural network uncertainty estimation☆69Updated 3 months ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆457Updated last year
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 2 months ago
- ☆152Updated 2 years ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆129Updated 3 years ago
- Code for Neural Spline Flows paper☆278Updated 5 years ago
- Parameter-Free Optimizers for Pytorch☆130Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Hessian spectral density estimation in TF and Jax☆123Updated 4 years ago
- Agustinus' very opiniated publication-ready plotting library☆69Updated 3 months ago
- Discrete Normalizing Flows implemented in PyTorch☆113Updated 3 years ago
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆227Updated 10 months ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆225Updated last year
- Materials of the Nordic Probabilistic AI School 2021.☆94Updated 4 years ago
- {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch☆215Updated 2 months ago