Stars
A curated list of awesome model based RL resources (continually updated)
An Optax-based JAX implementation of the IVON optimizer for large-scale VI training of NNs (ICML'24 spotlight)
Code for "The Memory Perturbation Equation: Understanding Model’s Sensitivity to Data", NeurIPS 2023.
IVON optimizer for neural networks based on variational learning.
Jax implementation for the paper "Sampling-based inference for large linear models, with application to linearised Laplace"
A simple Jax implementation of influence functions.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
kazukiosawa / minGPT_ASDL
Forked from karpathy/minGPTA minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.
Pytorch implementation of KFAC - this is a port of https://github.com/tensorflow/kfac/
Regression datasets from the UCI repository with standardized test-train splits.
PyTorch Library for Active Learning to accompany Human-in-the-Loop Machine Learning book
Evaluate three types of task shifting with popular continual learning algorithms.
Laplace Redux -- Effortless Bayesian Deep Learning
Marginal likelihood estimation for model selection in deep learning
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
A toolbox for trajectory optimization of dynamical systems
Implementation of different Relative Entropy Policy Search flavors