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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/TmacMai/CoMPILE_Inductive_Knowledge_Graph

공식 코드

Communicative Message Passing for Inductive Relation Reasoning

https://github.com/TongZhangTHU/sgr

공식 코드

Leveraging Locality to Boost Sample Efficiency in Robotic Manipulation

https://github.com/ToyotaResearchInstitute/packnet-sfm

공식 코드

3D Packing for Self-Supervised Monocular Depth Estimation

https://github.com/TsukamotoShuchi/ROCK

공식 코드

Recognizing Object by Components with Human Prior Knowledge Enhances Adversarial Robustness of Deep Neural Networks

https://github.com/UMBCvision/SSL-Backdoor

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Backdoor Attacks on Self-Supervised Learning

https://github.com/VanillaWhey/OCAtariWrappers

공식 코드

Deep Reinforcement Learning via Object-Centric Attention

https://github.com/ViTAE-Transformer/ViTAE-Transformer

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ViTAEv2: Vision Transformer Advanced by Exploring Inductive Bias for Image Recognition and Beyond

https://github.com/VictorProkhorov/HSVAE

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Learning Sparse Sentence Encoding without Supervision: An Exploration of Sparsity in Variational Autoencoders

https://github.com/Weber-GeoML/Unitary_Convolutions

공식 코드

Unitary convolutions for learning on graphs and groups

https://github.com/WenjieDu/PyPOTS

공식 코드

ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation

https://github.com/Wenxuan-1119/TransBTS

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TransBTSV2: Towards Better and More Efficient Volumetric Segmentation of Medical Images

https://github.com/Xingyu-Lin/VCD

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Learning Visible Connectivity Dynamics for Cloth Smoothing

https://github.com/Yang-Yuan/CPCNet

공식 코드

A Cognitively-Inspired Neural Architecture for Visual Abstract Reasoning Using Contrastive Perceptual and Conceptual Processing

https://github.com/YtongXie/CoTr

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CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation

https://github.com/YupuLu/ModLaNets

공식 코드

ModLaNets: Learning Generalisable Dynamics via Modularity and Physical Inductive Bias

https://github.com/ZhuoLinLi-shu/SDGL

공식 코드

Dynamic Graph Learning-Neural Network for Multivariate Time Series Modeling

https://github.com/ZidiXiu/CRT

공식 코드

Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer

https://github.com/ZiyiZhang27/tdpo

공식 코드

Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases

https://github.com/Zzzzz1/CSKD

공식 코드

Cumulative Spatial Knowledge Distillation for Vision Transformers

https://github.com/aadityasingh/tokenizationcounts

공식 코드

Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs

https://github.com/aagarwal1996/additive_trees

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A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds

https://github.com/aalto-quml/pipe

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Positional Encoding meets Persistent Homology on Graphs

https://github.com/aaltoml/generative-inverse-heat-dissipation

공식 코드

Generative Modelling With Inverse Heat Dissipation

https://github.com/aanna0701/SPT_LSA_ViT

공식 코드

Vision Transformer for Small-Size Datasets

https://github.com/aaronmueller/emergent-syntax

공식 코드

How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases

https://github.com/abdul2706/MaxViT-UNet

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MaxViT-UNet: Multi-Axis Attention for Medical Image Segmentation

https://github.com/achrefjaziri/decomposedencoders

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Representation Learning in a Decomposed Encoder Design for Bio-inspired Hebbian Learning

https://github.com/addtt/object-centric-library

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Generalization and Robustness Implications in Object-Centric Learning

https://github.com/adityalab/einns

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EINNs: Epidemiologically-informed Neural Networks

https://github.com/adlnlp/msg-chart

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MSG-Chart: Multimodal Scene Graph for ChartQA

https://github.com/adrianbzg/hyperbert

공식 코드

HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed Hypergraphs

https://github.com/adrianbzg/sqlformer

공식 코드

SQLformer: Deep Auto-Regressive Query Graph Generation for Text-to-SQL Translation

https://github.com/aeolusguan/NMRF

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Neural Markov Random Field for Stereo Matching

https://github.com/afoninandrei/opt-ml

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Can we learn gradients by Hamiltonian Neural Networks?

https://github.com/agentdr1/la_mil

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Local Attention Graph-based Transformer for Multi-target Genetic Alteration Prediction

https://github.com/ahmedesamy/leap

공식 코드

Leap: Inductive Link Prediction via Learnable TopologyAugmentation

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