Official PyTorch implementation of the paper: Flow Matching in Latent Space

Official PyTorch Implementation of "SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers"

[ICML 2025] Gaussian Mixture Flow Matching Models (GMFlow)

Easily and securely send things from one computer to another 🐊 📦

SNN Parallel Training

Update arXiv papers about Spiking Neural Networks daily.

《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持简中、繁中、English、日本語，提供 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 等代码实现

Supplementary materials and codes for the paper "Causal Structure Learning Supervised by Large Language Model"

Adversarial Counterfactual Temporal Inference Network

因果强化学习（迷宫环境）

Causal Transfer Learning

Official PyTorch implementation of Learning to (Learn at Test Time): RNNs with Expressive Hidden States

This repository will be posting analytic continual learning series, including Analytic Class-Incremental Learning (ACIL), Gaussian Kernel Embedded Analytic Learning (GKEAL), Dual-Stream Analytic Le…

Deep and online learning with spiking neural networks in Python

Offical implementation of "Adaptive Smoothing Gradient Learning for Spiking Neural Networks", ICML 2023

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[CELL PATTERNS] Official repo of Noisy Spiking Neural Networks

This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"

Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.

Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

Papers for Bayesian-NN