jidaivita / awesome-generalizable-world-models
Research papers on the mechanisms, generalization, and interpretability of learned world models.
jidaivita / awesome-generalizable-world-models
zju3dv / INTACT-JEPA
INTACT: Isomorphic Intent-to-Action Learning for Search-Free World Models.
OpenMOSS / OmniVAE
A unified audio-video variational autoencoder with cross-modal alignment for joint reconstruction and generation
Ma-Lab-Berkeley / deep-representation-learning-book
Learning Deep Representations of Data Distributions
c2g-dev / city2graph
Transform geospatial relations into graphs for Graph Neural Networks and spatial network analysis
marlin-codes / Awesome-Hyperbolic-Representation-and-Deep-Learning
Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
naganandy / graph-based-deep-learning-literature
links to conference publications in graph-based deep learning
yueliu1999 / Awesome-Deep-Graph-Clustering
[IEEE T-KDE 2026] Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
TIGER-AI-Lab / VLM2Vec
This repo contains the code for "VLM2Vec / MMEB" [ICLR 2025], "VLM2Vec-V2 / MMEB-V2" [TMLR 2026], and "MMEB-V3" [COLM 2026]
NiluK / worldmodels101
Free interactive course on world models in AI. Nine visual chapters on prediction, latent dynamics, planning, JEPA, video models, and failure modes.