Popular GitHub Repositories for Entropy Regularizer

Private & local AI personal knowledge management app for high entropy people.

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

Pytorch implementation of High-Fidelity Generative Image Compression + Routines for neural image compression

The Entropy Mechanism of Reinforcement Learning for Large Language Model Reasoning.

PyTorch Explain: Interpretable Deep Learning in Python.

[CVPR'20] Implementation for the paper "ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation"

Evaluate your dialog model with 17 metrics! (see paper)

[Materials & Design 2024] A Bayesian global optimization package for material design ｜ Adaptive Learning | Active Learning

LLM steganography with minimum-entropy coupling - Hiding encrypted messages in natural language.

Code lab for deep learning. Including rnn,seq2seq,word2vec,cross entropy,bidirectional rnn,convolution operation,pooling operation,InceptionV3,transfer learning.

klmbr - a prompt pre-processing technique to break through the barrier of entropy while generating text with LLMs

Probabilistic question-asking system: the program asks, the users answer. The minimal goal of the program is to identify what the user needs (a target), even if the user is not aware of the existence of such a thing/product/service.

Structural Entropy Guided Agent for Detecting and Repairing Knowledge Deficiencies in LLMs

Code for the AAAI 2022 publication "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"

Low dependency（C++11 STL only）, good portability, header-only, deep neural networks for embedded

The code of paper Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. Zhanqiu Zhang, Jianyu Cai, Jie Wang. NeurIPS 2020.

Implementation of key concepts of neuralnetwork via numpy

ExeShield AI detects malicious Windows executables using ML. Analyzes entropy, imports, and metadata for rapid classification, aiding incident response. Built with Python and scikit-learn.

PyTorch implementation of the Munchausen Reinforcement Learning Algorithms M-DQN and M-IQN