High-performance implementations of several reinforcement learning algorithms and some commonly used benchmark problems (Matlab & C++)
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Updated
Oct 12, 2017 - MATLAB
High-performance implementations of several reinforcement learning algorithms and some commonly used benchmark problems (Matlab & C++)
Actor Critic using Kronecker-Factored Trust Region
TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
Natural Gradient, Variational Inference
Project definition and implementations for Convex Optimization Course
Simple Experiments mainly on Machine Learning
My Master's Thesis on Variational Optimization of Neural Networks written at the Technical University of Denmark
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
(EvoApps2022) "Towards a Principled Learning Rate Adaptation for Natural Evolution Strategies"
Faster large mini-batch distributed training w/o. squeezing devices
Matrix-multiplication-only KFAC; Code for ICML 2023 paper on Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning
(CEC2023 Tutorial) Foundations and Recent Advances on Natural Evolution Strategies
Code for the paper "Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift"
(CEC2022) Fast Moving Natural Evolution Strategy for High-Dimensional Problems
Natural Gradient Boosting for Probabilistic Prediction
About A collection of AWESOME things about information geometry Topics
Gaussian Process package based on data augmentation, sparsity and natural gradients
Approximate Natural Gradient Descent with precision weighted predictive coding
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