wealone1's Stars
sindresorhus/awesome
😎 Awesome lists about all kinds of interesting topics
openai/CLIP
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
amusi/CVPR2024-Papers-with-Code
CVPR 2024 论文和开源项目合集
phidatahq/phidata
Build AI Agents with memory, knowledge, tools and reasoning. Chat with them using a beautiful Agent UI.
roboticcam/machine-learning-notes
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习,概率模型和深度学习的讲义(2000+页)和视频链接
iyaja/llama-fs
A self-organizing file system with llama 3
brunosimon/my-room-in-3d
MrForExample/ComfyUI-3D-Pack
An extensive node suite that enables ComfyUI to process 3D inputs (Mesh & UV Texture, etc) using cutting edge algorithms (3DGS, NeRF, etc.)
median-research-group/LibMTL
A PyTorch Library for Multi-Task Learning
JunweiLiang/awesome_lists
Awesome Lists for Tenure-Track Assistant Professors and PhD students. (助理教授/博士生生存指南)
OpenGVLab/InternVideo
[ECCV2024] Video Foundation Models & Data for Multimodal Understanding
SimonVandenhende/Multi-Task-Learning-PyTorch
PyTorch implementation of multi-task learning architectures, incl. MTI-Net (ECCV2020).
familyld/Awesome-Best-Papers
Collect awesome best papers from top AI conferences.
easezyc/Multitask-Recommendation-Library
MTReclib provides a PyTorch implementation of multi-task recommendation models and common datasets.
srebuffi/residual_adapters
sachit-menon/classify_by_description_release
robi56/video-summarization-resources
Video Summarization Dataset, Papers, Codes
HanxunH/Unlearnable-Examples
[ICLR2021] Unlearnable Examples: Making Personal Data Unexploitable
lhfowl/adversarial_poisons
MedMNIST/experiments
Codebase for reproducible benchmarking experiments in MedMNIST v2
fshp971/robust-unlearnable-examples
[ICLR 2022] Official repository for "Robust Unlearnable Examples: Protecting Data Against Adversarial Learning"
seriousran/awesome-video-sum
A curated list of the Video Summarization subject which is a computer science using machine learning and deep learning
StefanoWoerner/medimeta-pytorch
The medical imaging meta-learning toolbox allows to build models that learn to learn in a setting with diverse tasks. It also provides code for working with the MIMeta Dataset as well as simple baselines.
sutd-visual-computing-group/Re-thinking_MI
[CVPR-2023] Re-thinking Model Inversion Attacks Against Deep Neural Networks
jiamingzhang94/Unlearnable-Clusters
CVPR2023: Unlearnable Clusters: Towards Label-agnostic Unlearnable Examples
psandovalsegura/autoregressive-poisoning
Code for the paper "Autoregressive Perturbations for Data Poisoning" (NeurIPS 2022)
KrishnaswamyLab/CUTS
[MICCAI 2024] CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation
sdoerrich97/rethinking-model-prototyping-MedMNISTPlus
Official code repository for the paper "Rethinking Model Prototyping through the MedMNIST+ Dataset Collection"
EuterpeK/Rethinking-Data-Availability-Attacks
The code of ''Re-thinking Data Availability Attacks Against Deep Neural Networks''
MIRACLE-Center/Hierarchical_Feature_Constraint
MICCAI 2021 (early accpted), offical code for "A Hierarchical Feature Constraint to CamouflageMedical Adversarial Attacks"