timrudner
PhD Candidate in Computer Science, University of Oxford. Member of @OATML and @OxMLCS. Supervised by @yaringal and @ywteh.
Oxford, UK
timrudner's Stars
ssydasheng/FBNN
Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
thu-ml/zhusuan
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
cambridge-mlg/sghmc_dgp
chris-nemeth/pseudo-extended-mcmc-code
Code related to the paper "Pseudo-extended Markov chain Monte Carlo" by Christopher Nemeth, Fredrik Lindsten, Maurizio Filippone and James Hensman
oxwhirl/smac
SMAC: The StarCraft Multi-Agent Challenge
facebookresearch/nevergrad
A Python toolbox for performing gradient-free optimization
FrontierDevelopmentLab/multi3net
Multi3Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery
jakesnell/prototypical-networks
Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
Machine-Learning-Tokyo/DL-workshop-series
Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT)
jamesrobertlloyd/cbl-tikz-poster
A tikz based poster template for CBL.
xuehy/pytorch-mace
A pytorch implementation of Structured Exploration via Deep Hierarchical Coordination
aqlaboratory/proteinnet
Standardized data set for machine learning of protein structure
aqlaboratory/rgn
Recurrent Geometric Networks for end-to-end differentiable learning of protein structure
google-deepmind/trfl
TensorFlow Reinforcement Learning
google-deepmind/neural-processes
This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural Processes (NPs), Attentive Neural Processes (ANPs).
otokonoko8/deep-Bayesian-nonparametrics-papers
The collection of papers about combining deep learning and Bayesian nonparametrics
Santara/stochastic_value_gradient
Implementation of (Learning Continuous Control Policies by Stochastic Value Gradients)[https://arxiv.org/abs/1510.09142]
berkeleydeeprlcourse/homework
Assignments for CS294-112.
Svalorzen/AI-Toolbox
A C++ framework for MDPs and POMDPs with Python bindings
kchua/handful-of-trials
Experiment code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"
google/dopamine
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
rail-berkeley/rlkit
Collection of reinforcement learning algorithms
haarnoja/softqlearning
Reinforcement Learning with Deep Energy-Based Policies
haarnoja/sac
Soft Actor-Critic
Silvicek/distributional-dqn
Implementation of 'A Distributional Perspective on Reinforcement Learning' and 'Distributional Reinforcement Learning with Quantile Regression' based on OpenAi DQN baselines.
pytorch/ELF
ELF: a platform for game research with AlphaGoZero/AlphaZero reimplementation
yaringal/DropoutUncertaintyCaffeModels
Dropout As A Bayesian Approximation: Code
yaringal/BayesianRNN
Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"
sisl/MADRL
Repo containing code for multi-agent deep reinforcement learning (MADRL).
soumith/ganhacks
starter from "How to Train a GAN?" at NIPS2016