ae-foster
Sr Researcher @ Microsoft, former Oxford DPhil student in Statistical Machine Learning
Oxford, UK
ae-foster's Stars
microsoft/co-bed
CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design
fbickfordsmith/epig
Bayesian active learning with EPIG data acquisition
deepqmc/deepqmc
Deep learning quantum Monte Carlo for electrons in real space
microsoft/csuite
CSuite: A Suite of Benchmark Datasets for Causality
csiro-mlai/RL-BOED
BenevolentAI/CoMP
CoMP: Contrastive Mixture of Posteriors
oxcsml/riemannian-score-sde
Score-based generative models for compact manifolds
EmilienDupont/coinpp
Pytorch implementation of COIN++ 🍁
desi-ivanova/idad
Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
microsoft/mup
maximal update parametrization (µP)
google-research/arxiv-latex-cleaner
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
microsoft/project-azua
Data Efficient Decision Making
ae-foster/cresp
Code for 'On Contrastive Representations of Stochastic Processes' https://arxiv.org/abs/2106.10052
py-why/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
ae-foster/dad
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
mcmanigle/OxThesis
LaTeX template for an Oxford University thesis
iShohei220/torch-gqn
PyTorch Implementation of Generative Query Network
stan-dev/stan
Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
facebookresearch/swav
PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882
ae-foster/invclr
Improving Transformation Invariance in Contrastive Representation Learning
rattaoup/spirograph
Spirograph dataset from Improving Transformation Invariance in Contrastive Representation Learning
arogozhnikov/einops
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
stevenkleinegesse/seqbed
apple/ml-equivariant-neural-rendering
pyro-ppl/pyro-models
Repository of models in Pyro
talesa/slurm_gpustat
A simple command line tool to show GPU usage on a SLURM cluster
Goda-Research-Group/MLMC_stochastic_gradient
The codes used for the numerical experiments in the paper(https://arxiv.org/abs/2005.08414)
y0ast/slurm-for-ml
A Machine Learning workflow for Slurm.
pytorch/botorch
Bayesian optimization in PyTorch
ae-foster/pytorch-simclr
A PyTorch reproduction of 'A Simple Framework for Contrastive Learning of Visual Representations' by Ting Chen, et al.