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Official Python inference and LoRA trainer package for the LTX-2 audio–video generative model.
A unified media (Image, Video, Audio, Text) diffusion repository, for education and learning.
Official implementation of "Proactive Model Adaptation Against Concept Drift for Online Time Series Forecasting" (KDD'25), a novel online time series forecasting framework.
Graph learning framework for long-term video understanding
An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System
This repository implements variational graph auto encoder by Thomas Kipf.
Implementation of Graph Auto-Encoders in TensorFlow
PyTorch Implementation of "Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting" (AAAI2025)
[VLDB 2024] A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis
This is an official PyTorch implementation of "Continuous Evolution Pool: Taming Recurring Concept Drift in Online Time Series Forecasting"
An Extendible (General) Continual Learning Framework based on Pytorch - official codebase of Dark Experience for General Continual Learning
Official code for "Continual Learning in the Frequency Domain" (NeurIPS 2024)
[KDD2024] Class-incremental Learning for Time Series: Benchmark and Evaluation
🔥 Official impl. of "DetailFlow: 1D Coarse-to-Fine Autoregressive Image Generation via Next-Detail Prediction"
A list of recent papers about Link Prediction.
[NeurIPS'24] Supra-Laplacian Encoding for Transformer on Dynamic Graphs
Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.
Advances on machine learning of graphs, covering the reading list of recent top academic conferences.
[AAAI 2025] Official Implementation of "Auto-Regressive Moving Diffusion Models for Time Series Forecasting"
An implementation of the Autoregressive Diffusion Model for Graph Generation from [Kong et al. 2023]
Official implementation of Diffusion Graph Networks (DGNs)
[CVPR 2024] This is the official implementation of "ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction"
Official implementation of the paper "CSAD: Unsupervised Component Segmentation for Logical Anomaly Detection."
Efficient vision foundation models for high-resolution generation and perception.