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chunfeng114
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🦜🔗 Build context-aware reasoning applications
A latent text-to-image diffusion model
A guidance language for controlling large language models.
Instruct-tune LLaMA on consumer hardware
This repository contains implementations and illustrative code to accompany DeepMind publications
High-Resolution Image Synthesis with Latent Diffusion Models
LAVIS - A One-stop Library for Language-Vision Intelligence
My blogs and code for machine learning. http://cnblogs.com/pinard
李宏毅2021/2022/2023春季机器学习课程课件及作业
A simplified implemention of Faster R-CNN that replicate performance from origin paper
Materials for the Hugging Face Diffusion Models Course
Benchmarking large language models' complex reasoning ability with chain-of-thought prompting
A Unified Library for Parameter-Efficient and Modular Transfer Learning
The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。
[ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models
Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop
Solutions of Reinforcement Learning, An Introduction
温州大学《机器学习》课程资料（代码、课件等）
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0
Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
The Pytorch Tutorial of Score-based and Diffusion Model
WeChat Official Accounts, zhihu and CSDN'blog code
Official repository for "Revisiting Weakly Supervised Pre-Training of Visual Perception Models". https://arxiv.org/abs/2201.08371.
A PyTorch implementation for Unsupervised Domain Adaptation by Backpropagation
[CVPR 2024] LION: Empowering Multimodal Large Language Model with Dual-Level Visual Knowledge
[ECCV 2022] A generalized long-tailed challenge that incorporates both the conventional class-wise imbalance and the overlooked attribute-wise imbalance within each class. The proposed IFL together…
The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)