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Inductive Bias

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/yaorz97/parenet

공식 코드

PARE-Net: Position-Aware Rotation-Equivariant Networks for Robust Point Cloud Registration

https://github.com/yhlleo/VTs-Drloc

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Efficient Training of Visual Transformers with Small Datasets

https://github.com/yhygao/UTNet

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UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation

https://github.com/yhygao/cbim-medical-image-segmentation

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A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

https://github.com/yijia-xiao/pgraphdta

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PGraphDTA: Improving Drug Target Interaction Prediction using Protein Language Models and Contact Maps

https://github.com/yikangshen/Ordered-Neurons

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Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks

https://github.com/yingcong-li/transformers-as-algorithms

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Transformers as Algorithms: Generalization and Stability in In-context Learning

https://github.com/yingyichen-cyy/Nested-Co-teaching

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Compressing Features for Learning with Noisy Labels

https://github.com/yiwenwang03/syntactic-generalization-mandarin

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Controlled Evaluation of Grammatical Knowledge in Mandarin Chinese Language Models

https://github.com/yjlolo/dseq-vae

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Towards Robust Unsupervised Disentanglement of Sequential Data -- A Case Study Using Music Audio

https://github.com/yjyddq/CLAVER

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Kronecker Mask and Interpretive Prompts are Language-Action Video Learners

https://github.com/ymy-k/dptext-detr

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DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer

https://github.com/yonilc/ecct

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Error Correction Code Transformer

https://github.com/youqingxiaozhua/apvit

공식 코드

Vision Transformer with Attentive Pooling for Robust Facial Expression Recognition

https://github.com/yu-group/imodels-experiments

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Fast Interpretable Greedy-Tree Sums

https://github.com/yuchuantian/u-dit

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U-DiTs: Downsample Tokens in U-Shaped Diffusion Transformers

https://github.com/yue-zhongqi/diti

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Exploring Diffusion Time-steps for Unsupervised Representation Learning

https://github.com/yue-zhongqi/tif

공식 코드

Few-shot Learner Parameterization by Diffusion Time-steps

https://github.com/yueqirex/modsar

공식 코드

Your Causal Self-Attentive Recommender Hosts a Lonely Neighborhood

https://github.com/yueqirex/sar-check

공식 코드

Your Causal Self-Attentive Recommender Hosts a Lonely Neighborhood

https://github.com/yueqirex/self-attention-direction-check

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Your Causal Self-Attentive Recommender Hosts a Lonely Neighborhood

https://github.com/yuleiniu/introd

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Introspective Distillation for Robust Question Answering

https://github.com/yupeiyu98/deep-region-competition

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Unsupervised Foreground Extraction via Deep Region Competition

https://github.com/yupeiyu98/drc

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Unsupervised Foreground Extraction via Deep Region Competition

https://github.com/yuri-k111/bi-lipschitz-neural-network

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A provable control of sensitivity of neural networks through a direct parameterization of the overall bi-Lipschitzness

https://github.com/yuweisunn/associative-transformer

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Associative Transformer

https://github.com/yuxumin/PoinTr

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PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers

https://github.com/yyzharry/simper

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SimPer: Simple Self-Supervised Learning of Periodic Targets

https://github.com/zalandoresearch/gpa

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Grid Partitioned Attention: Efficient TransformerApproximation with Inductive Bias for High Resolution Detail Generation

https://github.com/zehong-wang/simmlp

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SimMLP: Training MLPs on Graphs without Supervision

https://github.com/zhaofengwu/rfa-doc-mt

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Modeling Context With Linear Attention for Scalable Document-Level Translation

https://github.com/zhaoyd1/dep_transformer_grammars

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Dependency Transformer Grammars: Integrating Dependency Structures into Transformer Language Models

https://github.com/zhaoziheng/k-space-transformer

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K-Space Transformer for Undersampled MRI Reconstruction

https://github.com/zhengchen1999/cat

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Cross Aggregation Transformer for Image Restoration

https://github.com/zhuang-group/spvit

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Pruning Self-attentions into Convolutional Layers in Single Path

https://github.com/zhuangdizhu/FedGen

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Data-Free Knowledge Distillation for Heterogeneous Federated Learning

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