Lists (3)
Sort Name ascending (A-Z)
Stars
FinRL®-Meta: Dynamic datasets and market environments for FinRL.
A RWKV management and startup tool, full automation, only 8MB. And provides an interface compatible with the OpenAI API. RWKV is a large language model that is fully open source and available for c…
The definitive Web UI for local AI, with powerful features and easy setup.
This is a workshop designed for Amazon Bedrock a foundational model service.
Existing Literature about Machine Unlearning
Starting kit for the NeurIPS 2023 unlearning challenge
Giggfitnesse / PyXAB
Forked from WilliamLwj/PyXABPyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms
🔥 基于 Laravel 的后台系统构建工具 (Laravel Admin),使用很少的代码快速构建一个功能完善的高颜值后台系统,内置丰富的后台常用组件,开箱即用,让开发者告别冗杂的HTML代码
slideslive slides downloading script
Notebooks and examples on how to onboard and use various features of Amazon Forecast.
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms
Partially Adaptive Momentum Estimation method in the paper "Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks" (accepted by IJCAI 2020)
AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights (ICLR 2021)
NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.
The original implementation of the experiments in the paper of AdaShift (See https://arxiv.org/abs/1810.00143)
Repository for NeurIPS 2020 Spotlight "AdaBelief Optimizer: Adapting stepsizes by the belief in observed gradients"
[IJCAI'19] Nostalgic Adam: Weighting more of the past gradients when designing the adaptive learning rate
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Demonstrate all the questions on LeetCode in the form of animation.(用动画的形式呈现解LeetCode题目的思路)
LSTM and QRNN Language Model Toolkit for PyTorch
Acceptance rates for the major AI conferences