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Mutual Information Estimation
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To estimate mutual information from samples, specially for high-dimensional variables.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BorealisAI/BMI
공식 코드Better Long-Range Dependency By Bootstrapping A Mutual Information Regularizer
https://github.com/MustaphaBounoua/minde
공식 코드https://github.com/RayRuizhiLiao/mutual_info_img_txt
공식 코드Multimodal Representation Learning via Maximization of Local Mutual Information
https://github.com/anonymous1252022/kr_for_gnns
공식 코드https://github.com/anonymous1252022/recoverability
공식 코드https://github.com/blackPython/mi_estimator
공식 코드https://github.com/cbg-ethz/bmi
공식 코드On the Properties and Estimation of Pointwise Mutual Information Profiles
https://github.com/ccha23/MI-NEE
공식 코드Neural Entropic Estimation: A faster path to mutual information estimation
https://github.com/chnq/tracingllm
공식 코드Towards Tracing Trustworthiness Dynamics: Revisiting Pre-training Period of Large Language Models
https://github.com/csyanbin/LSMI-Sinkhorn
공식 코드LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport
https://github.com/dwdavidxd/miat
공식 코드Improving Adversarial Robustness via Mutual Information Estimation
https://github.com/ermongroup/dre-infinity
공식 코드https://github.com/ermongroup/f-dre
공식 코드https://github.com/google-research/google-research
공식 코드https://github.com/hamrel-cxu/flowot
공식 코드Computing high-dimensional optimal transport by flow neural networks
https://github.com/huangsicong/ais_mi_estimation
공식 코드Improving Mutual Information Estimation with Annealed and Energy-Based Bounds
https://github.com/kxytechnologies/kxy-python
공식 코드MIND: Inductive Mutual Information Estimation, A Convex Maximum-Entropy Copula Approach
https://github.com/lehaifeng/T-GCN
공식 코드Augmentation-Free Graph Contrastive Learning of Invariant-Discriminative Representations
https://github.com/lijuntaopku/UFD
공식 코드Unsupervised Domain Adaptation of a Pretrained Cross-Lingual Language Model
https://github.com/louey233/toward-mutual-information
공식 코드https://github.com/majianthu/copent
공식 코드https://github.com/navneet-nmk/pytorch-rl
공식 코드Empowerment-driven Exploration using Mutual Information Estimation
https://github.com/nicolasigor/entropy
공식 코드https://github.com/qingguo666/FLO
공식 코드Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization
https://github.com/rdevon/DIM
공식 코드Learning deep representations by mutual information estimation and maximization
https://github.com/rezafuru/frankensplit
공식 코드https://github.com/sysbiosig/capacity-of-canonical-models
공식 코드Closed-Form Information Capacity of Canonical Signaling Models
https://github.com/tonellolab/codine-copula-estimator
공식 코드https://github.com/tonellolab/fdime
공식 코드Mutual Information Estimation via $f$-Divergence and Data Derangements
https://github.com/uk-cliplab/DiME
공식 코드DiME: Maximizing Mutual Information by a Difference of Matrix-Based Entropies
https://github.com/yuchen005/robustger
공식 코드Large Language Models are Efficient Learners of Noise-Robust Speech Recognition
https://github.com/yujieouo/smie
공식 코드Zero-shot Skeleton-based Action Recognition via Mutual Information Estimation and Maximization
https://github.com/zfan20/mstein
공식 코드Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation
https://github.com/DuaneNielsen/DeepInfomaxPytorch
Learning deep representations by mutual information estimation and maximization
https://github.com/HolenYHR/Deepinfo_pytorch
Learning deep representations by mutual information estimation and maximization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.