oatml Goto Github PK

batchbald

Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning.

bdl-benchmarks

Bayesian Deep Learning Benchmarks

causal-bald

clouds

Exploring the effects of aerosols on proxies for cloud reflectivity

deterministic-uncertainty-quantification

Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"

eve

Official repository for the paper "Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning". Joint collaboration between the Marks lab and the OATML group.

non-parametric-transformers

Code for "Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning"

nppt

Working code for non parametric protein transformer for bayesian optimisation

oatomobile

A research framework for autonomous driving

overcast

Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions

quince

Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding

radial_bnn

Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning

rho-loss

snr_issues_in_deep_gps

On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes

tfpyth

Putting TensorFlow back in PyTorch, back in TensorFlow (differentiable TensorFlow PyTorch adapters).

ucate

Uncertainty in Conditional Average Treatment Effect Estimation