Approximate Natural Gradient Descent with precision weighted predictive coding
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Updated
Apr 20, 2024 - Python
Approximate Natural Gradient Descent with precision weighted predictive coding
Gaussian Process package based on data augmentation, sparsity and natural gradients
About A collection of AWESOME things about information geometry Topics
Natural Gradient Boosting for Probabilistic Prediction
(CEC2022) Fast Moving Natural Evolution Strategy for High-Dimensional Problems
Code for the paper "Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift"
(CEC2023 Tutorial) Foundations and Recent Advances on Natural Evolution Strategies
Matrix-multiplication-only KFAC; Code for ICML 2023 paper on Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning
Faster large mini-batch distributed training w/o. squeezing devices
(EvoApps2022) "Towards a Principled Learning Rate Adaptation for Natural Evolution Strategies"
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).
My Master's Thesis on Variational Optimization of Neural Networks written at the Technical University of Denmark
Simple Experiments mainly on Machine Learning
Project definition and implementations for Convex Optimization Course
Natural Gradient, Variational Inference
TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
Actor Critic using Kronecker-Factored Trust Region
High-performance implementations of several reinforcement learning algorithms and some commonly used benchmark problems (Matlab & C++)
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