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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/martinferianc/ComBiNet
공식 코드ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation
https://github.com/martinferianc/quantised-bayesian-nets
공식 코드On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks
https://github.com/martius-lab/zilot
공식 코드https://github.com/marvinschmitt/ModelMisspecificationBF
공식 코드Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks
https://github.com/marvinsxtr/explainable-cell-graphs
공식 코드xCG: Explainable Cell Graphs for Survival Prediction in Non-Small Cell Lung Cancer
https://github.com/mathieurenault1/sar-unet
공식 코드SAR-UNet: Small Attention Residual UNet for Explainable Nowcasting Tasks
https://github.com/mathieutuli/ltl-gata
공식 코드https://github.com/matteo-rizzo/saliency-faithfulness-eval
공식 코드https://github.com/matthijsdej/gnn_pn_imitation_learning
공식 코드Generalizable Graph Neural Networks for Robust Power Grid Topology Control
https://github.com/matthijsdej/imitation_learning_topology_control
공식 코드Imitation Learning for Intra-Day Power Grid Operation through Topology Actions
https://github.com/mattswatson/attack-agnostic-adversarial-attack-detection
공식 코드Attack-agnostic Adversarial Detection on Medical Data Using Explainable Machine Learning
https://github.com/maups/covid19-satellite-analysis
공식 코드https://github.com/mavridischristos/onlinedeterministicannealing
공식 코드https://github.com/max7born/decision-lstm
공식 코드https://github.com/maxdreyer/crp-human-study
공식 코드From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation
https://github.com/maxdreyer/pcx
공식 코드https://github.com/maxdreyer/reveal2revise
공식 코드Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models
https://github.com/maximecb/gym-miniworld
공식 코드Avoidance Learning Using Observational Reinforcement Learning
https://github.com/maximelenormand/OWA-weights-generator
공식 코드https://github.com/maximilianigl/DVRL
공식 코드https://github.com/maximilienlc/gane
공식 코드Generative Adversarial Neuroevolution for Control Behaviour Imitation
https://github.com/maxlampe/mentat
공식 코드https://github.com/maxnaeg/zxreinforce
공식 코드https://github.com/maxramgraber/triangular-transport-toolbox
공식 코드https://github.com/maxwell1447/fairseq
공식 코드Towards Example-Based NMT with Multi-Levenshtein Transformers
https://github.com/mayer123/laser
공식 코드LASER: LLM Agent with State-Space Exploration for Web Navigation
https://github.com/maytusp/triplet_search
공식 코드https://github.com/mayunyi-1999/traffnet_code
공식 코드TraffNet: Learning Causality of Traffic Generation for What-if Prediction
https://github.com/mbchang/crl
공식 코드Automatically Composing Representation Transformations as a Means for Generalization
https://github.com/mbeliaev1/irleed
공식 코드Inverse Reinforcement Learning by Estimating Expertise of Demonstrators
https://github.com/mbithenzomo/semantic_phms_mapping_study
공식 코드https://github.com/mch5048/gatsbi
공식 코드GATSBI: Generative Agent-centric Spatio-temporal Object Interaction
https://github.com/mchancan/citylearn
공식 코드CityLearn: Diverse Real-World Environments for Sample-Efficient Navigation Policy Learning
https://github.com/meaten/motionaug
공식 코드MotionAug: Augmentation with Physical Correction for Human Motion Prediction
https://github.com/medgift/iMIMIC-RCVs
공식 코드Regression Concept Vectors for Bidirectional Explanations in Histopathology
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.