Papers with Code 아카이브

Computational Efficiency

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보존된 평가 기록: 1

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

코드

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

https://github.com/itsowen/betternet

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BetterNet: An Efficient CNN Architecture with Residual Learning and Attention for Precision Polyp Segmentation

https://github.com/iyerkrithika21/Mesh2SSMJournal

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Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes

https://github.com/jLooo/VADMamba

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VADMamba: Exploring State Space Models for Fast Video Anomaly Detection

https://github.com/jackfrost168/cf_diff

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Collaborative Filtering Based on Diffusion Models: Unveiling the Potential of High-Order Connectivity

https://github.com/jackliu-97/bginet

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Remote Sensing Image Change Detection with Graph Interaction

https://github.com/jacob-parnell-rozetta/longformer_coverage

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A Multi-Document Coverage Reward for RELAXed Multi-Document Summarization

https://github.com/jajajang/lowpopart

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Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits

https://github.com/james0223/p-hologen

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P-Hologen: An End-to-End Generative Framework for Phase-Only Holograms

https://github.com/jangminhyuk/steadystatedrkf

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On the Steady-State Distributionally Robust Kalman Filter

https://github.com/jaredfern/framework-tax

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The Framework Tax: Disparities Between Inference Efficiency in NLP Research and Deployment

https://github.com/jasmina-karabegovic/irgames

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An algorithm for two-player repeated games with imperfect public monitoring

https://github.com/jbrich95/pinnev

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Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networks

https://github.com/jeffwillette/cascading_kv_cache

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Training-Free Exponential Context Extension via Cascading KV Cache

https://github.com/jeremy-goldwasser/feature-rankings

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Statistical Significance of Feature Importance Rankings

https://github.com/jeremy-goldwasser/rankshap

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Statistical Significance of Feature Importance Rankings

https://github.com/jeromerony/augmented_lagrangian_adversarial_attacks

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Augmented Lagrangian Adversarial Attacks

https://github.com/jesusdaniel/spcaCD

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Overlapping community detection in networks via sparse spectral decomposition

https://github.com/jhu-clsp/science-hierarchography

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Science Hierarchography: Hierarchical Organization of Science Literature

https://github.com/jiacheng8/fadrm

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FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation

https://github.com/jiahaowork/idam

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Iterative Distance-Aware Similarity Matrix Convolution with Mutual-Supervised Point Elimination for Efficient Point Cloud Registration

https://github.com/jianghaojun/CondenseNetV2

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CondenseNet V2: Sparse Feature Reactivation for Deep Networks

https://github.com/jiaqileng/gradient-based-qhd

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Quantum Optimization via Gradient-Based Hamiltonian Descent

https://github.com/jiarunliu/biovfm

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BioVFM-21M: Benchmarking and Scaling Self-Supervised Vision Foundation Models for Biomedical Image Analysis

https://github.com/jiawei-mo/3d_place_recognition

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A Fast and Robust Place Recognition Approach for Stereo Visual Odometry Using LiDAR Descriptors

https://github.com/jiaweihhuang/heuristic_mebp

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Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL

https://github.com/jiaweihhuang/rlhf_rewardtransfer

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Can RLHF be More Efficient with Imperfect Reward Models? A Policy Coverage Perspective

https://github.com/jiaweizzhao/inrank

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InRank: Incremental Low-Rank Learning

https://github.com/jiexiong2016/GCNv2_SLAM

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GCNv2: Efficient Correspondence Prediction for Real-Time SLAM

https://github.com/jimengshi/codicast

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CoDiCast: Conditional Diffusion Model for Global Weather Prediction with Uncertainty Quantification

https://github.com/jin530/swalk

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S-Walk: Accurate and Scalable Session-based Recommendationwith Random Walks

https://github.com/jindeok/CA-GF

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Criteria-Aware Graph Filtering: Extremely Fast Yet Accurate Multi-Criteria Recommendation

https://github.com/jindeok/cpa-lgc-recbole

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Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation

https://github.com/jindongli-ai/survey_on_clip-powered_domain_generalization_and_adaptation

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CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey

https://github.com/jingjin25/LFASR-FS-GAF

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Deep Coarse-to-fine Dense Light Field Reconstruction with Flexible Sampling and Geometry-aware Fusion

https://github.com/jingnantes/hybrid-mst

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Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation

https://github.com/jingyechen/mt-transunet

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MT-TransUNet: Mediating Multi-Task Tokens in Transformers for Skin Lesion Segmentation and Classification

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.