Apply Waseerstein GAN into SRGAN, a deep learning super resolution model

GL-FNO - an enhanced Fourier neural operator-based deep-learning model for Accelerating Coronal Magnetic Field Model

Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021). Remaining useful l…

Boosting the AI research efficiency

Code related to SDO HMI dataset of active regions and flare activity.

DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia

Awesome LLM compression research papers and tools.

A latent text-to-image diffusion model

The official repository of BFSR: "Boosting Flow-based Generative Super-Resolution Models via Learned Prior" [CVPR 2024]

High-Resolution Image Synthesis with Latent Diffusion Models

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

A curated list of resources on implicit neural representations.

Flex-DLD: Deep Low-rank Decomposition Model with Flexible Priors for Hyperspectral Image Denoising and Restoration

A project page template for academic papers. Demo at https://eliahuhorwitz.github.io/Academic-project-page-template/

Awesome Machine Unlearning (A Survey of Machine Unlearning)

SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild. Our new online demo is also released at suppixel.ai.

Paper list and datasets for industrial image anomaly/defect detection (updating). 工业异常/瑕疵检测论文及数据集检索库(持续更新)。

Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."

[CVPR 2024] SinSR: Diffusion-Based Image Super-Resolution in a Single Step

This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.

Code for the paper "Poseidon: Efficient Foundation Models for PDEs"

AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning (ICLR 2023).

The source code of the EMNLP 2023 main conference paper: Sparse Low-rank Adaptation of Pre-trained Language Models.

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

Low-Rank Tensor Decomposition with Deep Network Priors

Pytorch implementation of our paper accepted by CVPR 2020 (Oral) -- HRank: Filter Pruning using High-Rank Feature Map

(ECCV'2020 Oral)EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning