Stars
[ICML Workshop 24 & AAAI 25] Denoising Pretraining Framework for Crystal Models
CrysMMNet: Multimodal Representation for Crystal Property Prediction (UAI-2023)
Tool for robust segmentation of >100 important anatomical structures in CT and MR images
Learnable Global Pooling Layers Based on Regularized Optimal Transport (ROT)
U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation
Code for paper "Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters" CVPR2024
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation (ICML'24 Oral)
[ICLR 2024 Oral] Supervised Pre-Trained 3D Models for Medical Image Analysis (9,262 CT volumes + 25 annotated classes)
[MedIA Best Paper Award] Official implementation of MedIA paper "BayeSeg: Bayesian Modelling for Medical Image Segmentation with Interpretable Generalizability"
[ICLR 2024 Spotlight] R-EDL: Relaxing Nonessential Settings of Evidential Deep Learning
[IEEE TMI-2024] UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation
ICCV2023 | Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation
We present a comprehensive and deep review of the HFM in challenges, opportunities, and future directions. The released paper: https://arxiv.org/abs/2404.03264
Implementations of recent research prototypes/demonstrations using MONAI.
AAAI 2024 Papers: Explore a comprehensive collection of innovative research papers presented at one of the premier artificial intelligence conferences. Seamlessly integrate code implementations for…
Official repository for "Orthogonal Projection Loss" (ICCV'21)
[CVPR 2024] The code repository for "Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning" in PyTorch.
Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.
A comprehensive benchmark of deepfake detection
Official implementation of Evidential Uncertainty Quantification: A Variance-Based Perspective [WACV 2024]
[ICLR 2023 Spotlight] Code release for "Dirichlet-based Uncertainty Calibration for Active Domain Adaptation"
PyTorch implementation of Barlow Twins.
Official implementation of the paper "Masked Autoencoders are Efficient Class Incremental Learners"
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, …
sender666 / PyCIL
Forked from LAMDA-CL/PyCILPyCIL: A Python Toolbox for Class-Incremental Learning