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Python
Last Updated
May 21, 2024
Similar Repos
| Repo | Language | Stars | Description | Updated At |
|---|---|---|---|---|
| Python | 13 | Official PyTorch implementation for our upcoming ICML 2023 paper, Regularization-free Diffeomorphic Temporal Alignment Nets. | Jun 04, 2023 | |
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| Jupyter Notebook | 44 | Official implementation of our paper: Towards Robust and Reproducible Active Learning using Neural Networks, accepted … | Apr 27, 2023 | |
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| Python | 2 | The official pytorch implementation of our paper "Boosted EfficientNet: Detection of Lymph Node Metastases in … | Jul 22, 2021 | |
| Python | 30 | Official implementation of GraphMask as presented in our paper Interpreting Graph Neural Networks for NLP … | May 13, 2023 | |
| Python | 38 | Official Python3 implementation of our ICML 2021 paper "Unbalanced minibatch Optimal Transport; applications to Domain … | Apr 16, 2023 | |
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| Python | 11 | Official implementation of our ICLR 2023 paper "Towards One-shot Neural Combinatorial Solvers: Theoretical and Empirical … | Apr 21, 2023 | |
| Python | 34 | Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks" | May 02, 2023 | |
| Python | 17 | The official implementation of the paper "Reconstructing QRS Complex from PPG by Transformed Attentional Neural … | Mar 17, 2023 | |
| Python | 47 | Official PyTorch implementation of Hyperbolic Neural Networks++ | Apr 26, 2023 | |
| Python | 3 | Official Code for our L4DC 2023 conference paper and ICLR 2023 NeSy-GeMs workshop paper. | Apr 23, 2023 | |
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| Python | 743 | official implementation for the paper "Simplifying Graph Convolutional Networks" | Apr 28, 2023 | |
| Python | 6 | Repository for the paper Tackling covariate shift with node-based Bayesian neural networks (ICML 2022) | Apr 22, 2023 | |
| Python | 25 | This is an official PyTorch implementation of the ICML 2023 paper 《AdaNPC: Exploring Non-Parametric Classifier … | May 03, 2023 | |
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| Python | 5 | This repository is the official implementation of our paper. | Sep 06, 2023 | |
| Jupyter Notebook | 103 | Official implementation of "Path Planning using Neural A* Search" (ICML-21) | May 07, 2023 | |
| Python | 2 | My own implementation of ICML 2019 paper: Set Transformer: A Framework for Attention-based Permutation-Invariant Neural … | Aug 25, 2021 | |
| Python | 23 | repo for our ICML 2023 paper "Input Perturbation Reduces Exposure Bias in Diffusion Models" | May 08, 2023 | |
| Python | 50 | official PyTorch implementation of paper "Continual Meta-Learning with Bayesian Graph Neural Networks" (AAAI2020) | Feb 21, 2023 | |
| Python | 2 | Official Pytorch implementation of paper "Zero Stability Well Predicts Performance of Convolutional Neural Networks" | Apr 17, 2023 | |
| Python | 28 | [CVPR'23] The official PyTorch implementation of our CVPR 2023 paper: "Generalized Relation Modeling for Transformer … | Apr 25, 2023 | |
| Python | 34 | [ICLR 2023] The official code for our ICLR 2023 (top25%) paper: "Neural Collapse Inspired Feature-Classifier … | Apr 27, 2023 | |
| Jupyter Notebook | 11 | Python Implementation of Linear Regression and Pseudo-inverse - Neural Networks | May 13, 2023 | |
| Python | 8 | Python/PyTorch code for the ICML 2021 Paper: Improving Gradient Regularization using Complex-Valued Neural Networks | May 10, 2022 | |
| Python | 100 | Official PyTorch implementation for "Image Restoration with Mean-Reverting Stochastic Differential Equations", ICML 2023 & CVPRW … | Apr 26, 2023 | |
| Python | 11 | Official implementation for paper "No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and … | Jan 09, 2024 | |
| Python | 32 | The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks" | Apr 19, 2023 | |
| Python | 21 | ICML'22: Local Augmentation for Graph Neural Networks | Aug 14, 2022 | |
| Python | 9 | The official implementation of our CVPR 2023 paper "Detecting Backdoors During the Inference Stage Based … | May 04, 2023 | |
| C++ | 342 | Implementation for <Large-Margin Softmax Loss for Convolutional Neural Networks> in ICML'16. | May 23, 2023 | |
| Python | 3 | Code for the ICML 2020 Paper ''Maximum-and-Concatenation Networks'' | Nov 25, 2020 |