lynne294's Stars
codecrafters-io/build-your-own-x
Master programming by recreating your favorite technologies from scratch.
Significant-Gravitas/AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
shap/shap
A game theoretic approach to explain the output of any machine learning model.
kenjihiranabe/The-Art-of-Linear-Algebra
Graphic notes on Gilbert Strang's "Linear Algebra for Everyone"
BlinkDL/RWKV-LM
RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
ShiArthur03/ShiArthur03
OptimalScale/LMFlow
An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
rui314/8cc
A Small C Compiler
bethgelab/foolbox
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
andreas128/RePaint
Official PyTorch Code and Models of "RePaint: Inpainting using Denoising Diffusion Probabilistic Models", CVPR 2022
MadryLab/robustness
A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.
vislearn/FrEIA
Framework for Easily Invertible Architectures
naoto0804/pytorch-inpainting-with-partial-conv
Unofficial pytorch implementation of 'Image Inpainting for Irregular Holes Using Partial Convolutions' [Liu+, ECCV2018]
abhijitjadhav1998/Deepfake_detection_using_deep_learning
This projects aims in detection of video deepfakes using deep learning techniques like RestNext and LSTM. We have achived deepfake detection by using transfer learning where the pretrained RestNext CNN is used to obtain a feature vector, further the LSTM layer is trained using the features. For more details follow the documentaion.
NVlabs/DiffPure
A new adversarial purification method that uses the forward and reverse processes of diffusion models to remove adversarial perturbations.
inspire-group/adv-patch-paper-list
A paper list for localized adversarial patch research
WangXinluan/ChatGPT-Academic
inspire-group/PatchGuard
Code for paper "PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking"
dydjw9/Efficient_SAM
LuChengTHU/mle_score_ode
Official code for "Maximum Likelihood Training for Score-Based Diffusion ODEs by High-Order Denoising Score Matching" (ICML 2022)
JinyiW/GuidedDiffusionPur
nmndeep/revisiting-at
[NeurIPS 2023] Code for the paper "Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models"
DequanWang/dent
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks
Harry24k/catastrophic-overfitting
Understanding Catastrophic Overfitting in Single-step Adversarial Training [AAAI 2021]
point0bar1/ebm-defense
PyTorch implementation of BPDA+EOT attack to evaluate adversarial defense with an EBM
RayDeeA/ibinn_imagenet
fra31/evaluating-adaptive-test-time-defenses
val-iisc/NuAT
Towards Efficient and Effective Adversarial Training, NeurIPS 2021
cyz-ai/attack_DGM
Codes for the ICML20' paper: On Breaking Deep Generative Model based Defenses and Beyond
DependableSystemsLab/Jujutsu
Code for the paper "Turning Your Strength against You: Detecting and Mitigating Robust and Universal Adversarial Patch Attack"