Popular GitHub Repositories for Permutation Entropy

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.

Adaptation of the merging method described in the paper - Git Re-Basin: Merging Models modulo Permutation Symmetries (https://arxiv.org/abs/2209.04836) for Stable Diffusion

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

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

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

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.

Official source code for "Graph Neural Networks for Learning Equivariant Representations of Neural Networks". In ICLR 2024 (oral).

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

[CVPR'21] SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Data, in PyTorch

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.

【AAAI2024】TOP-ReID: Multi-spectral Object Re-Identification with Token Permutation

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