Text-to-video generation: CogVideoX (2024) and CogVideo (ICLR 2023)

Parallel Frequent Subgraph Mining

RISC-V Cores, SoC platforms and SoCs

A reading list for deep graph learning acceleration.

PyTorch implementations of deep reinforcement learning algorithms and environments

A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

Code for "Fast Context Adaptation via Meta-Learning"

2D Gridworld navigation using RL with Hindsight Experience Replay

A toolkit for reproducible reinforcement learning research.

Code for the model presented in the paper "A Biologically Plausible Supervised Learning Method for Spiking Neural Networks Using the Symmetric STDP Rule"

Training spiking networks with hybrid ann-snn conversion and spike-based backpropagation

What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are…

Spatio-temporal BP for SNNs

Build your neural network easy and fast, 莫烦Python中文教学

Binarized Neural Network (BNN) for pytorch

Pure python implementation of SNN

Toolbox for converting analog to spiking neural networks (ANN to SNN), and running them in a spiking neuron simulator.

Spiking neural networks (SNNs) for speech classification

C++ Spiking Neural Network Simulator Framework

Reinforcement Learning for Spiking Neural Networks

Paper list for SNN based computer vision tasks.

A PyTorch implementation of Spiking-YOLOv3. Two branches are provided, based on two common PyTorch implementation of YOLOv3(ultralytics/yolov3 & eriklindernoren/PyTorch-YOLOv3), with support for Sp…

A tutorial on 'Soft weight-sharing for Neural Network compression' published at ICLR2017