Learning Deep Representations of Data Distributions

What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are…

Code for the paper "learning generalizable representations through efficient coding"

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKT…

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning

Author's PyTorch implementation of TD3 for OpenAI gym tasks

Simulation of spiking neural networks (SNNs) using PyTorch.

Deep and online learning with spiking neural networks in Python

Pure python implementation of SNN

MuJoCo fruit fly body model and locomotion RL tasks

Python package for automatic Gaussian mixture modeling

In this project, I implemented several ensemble methods (including bagging, AdaBoost, SAMME, stacking, snapshot ensemble) for a normal CNN model and Residual Neural Network.

A powerful Zotero AI and MCP plugin with ChatGPT, Gemini 3.1, Claude, Grok, DeepSeek, OpenRouter, Kimi 2.5, GLM 5, SiliconFlow, GPT-oss, Gemma 3, Qwen 3.5

Enhancing Chess Reinforcement Learning with Graph Representation

🧮 A collection of resources to learn mathematics for machine learning

Grandmaster-Level Chess Without Search

One-for-All Multimodal Evaluation Toolkit Across Text, Image, Video, and Audio Tasks

Maia-2 is a new human-like neural network chess engine trained on millions of human games.

Maia is a human-like neural network chess engine trained on millions of human games.

Chess books used to develop Stockfish

"SHAP-XRT: The Shapley Value Meets Conditional Independence Testing"

Scikit-learn compatible decision trees beyond those offered in scikit-learn

Companion webpage to the book "Mathematics For Machine Learning"