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Computational Efficiency

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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/viscom-ulm/GINN

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Deep-learning the Latent Space of Light Transport

https://github.com/vision4robotics/AMCF-tracker

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Augmented Memory for Correlation Filters in Real-Time UAV Tracking

https://github.com/vision4robotics/DCFTracking4UAV

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Correlation Filters for Unmanned Aerial Vehicle-Based Aerial Tracking: A Review and Experimental Evaluation

https://github.com/vivekoommen/NeuralOperator_DiffusionModel

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Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

https://github.com/vlgiitr/lora-unlearn

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LoRA Unlearns More and Retains More (Student Abstract)

https://github.com/volleyIEEE/VolleyStats

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Advanced Volleyball Stats for All Levels: Automatic Setting Tactic Detection and Classification with a Single Camera

https://github.com/vonguyenleduy/dnn_representation_selective_inference

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Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference

https://github.com/vonguyenleduy/dnn_segmentation_selective_inference

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Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference

https://github.com/voxelmorph/spheremorph

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Cortical surface registration using unsupervised learning

https://github.com/vturrisi/solo-learn

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All4One: Symbiotic Neighbour Contrastive Learning via Self-Attention and Redundancy Reduction

https://github.com/vvanirudh/lamps-mbrl

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The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms

https://github.com/w4k2/stream-learn

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stream-learn -- open-source Python library for difficult data stream batch analysis

https://github.com/wagnermoritz/SCFE

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S-CFE: Simple Counterfactual Explanations

https://github.com/wake1021/inceptionmamba

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InceptionMamba: An Efficient Hybrid Network with Large Band Convolution and Bottleneck Mamba

https://github.com/wanggynpuer/3d-rcnet

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3D-RCNet: Learning from Transformer to Build a 3D Relational ConvNet for Hyperspectral Image Classification

https://github.com/wanglimin/Places205-VGGNet

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Places205-VGGNet Models for Scene Recognition

https://github.com/wangnanwei/Birth-death-MCMC-Model-Selection

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The scalable Birth-Death MCMC Algorithm for Mixed Graphical Model Learning with Application to Genomic Data Integration

https://github.com/wangren09/mcgr

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Robust Mode Connectivity-Oriented Adversarial Defense: Enhancing Neural Network Robustness Against Diversified $\ell_p$ Attacks

https://github.com/wangshusen/RandMatrixMatlab

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A Practical Guide to Randomized Matrix Computations with MATLAB Implementations

https://github.com/wangyong1301108/mmpinn

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A practical PINN framework for multi-scale problems with multi-magnitude loss terms

https://github.com/wanjunhuang/hwjcode

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DeepOPF-V: Solving AC-OPF Problems Efficiently

https://github.com/warplab/DeepSeeColor

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DeepSeeColor: Realtime Adaptive Color Correction for Autonomous Underwater Vehicles via Deep Learning Methods

https://github.com/waterhorse1/CMML_pytorch

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CMML: Contextual Modulation Meta Learning for Cold-Start Recommendation

https://github.com/wbw520/rtfp

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Improving Facade Parsing with Vision Transformers and Line Integration

https://github.com/wdlctc/headinfer

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HeadInfer: Memory-Efficient LLM Inference by Head-wise Offloading

https://github.com/wehos/cellt

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Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data Imputation

https://github.com/weibaozhong/lgstime

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Innovative LSGTime Model for Crime Spatiotemporal Prediction Based on MindSpore Framework

https://github.com/weijiemax/lssinst

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LSSInst: Improving Geometric Modeling in LSS-Based BEV Perception with Instance Representation

https://github.com/weinajin/multimodal_explanation

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Guidelines and Evaluation of Clinical Explainable AI in Medical Image Analysis

https://github.com/weipengoo98/rang_pinn

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RANG: A Residual-based Adaptive Node Generation Method for Physics-Informed Neural Networks

https://github.com/weitunglin/pixmamba

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PixMamba: Leveraging State Space Models in a Dual-Level Architecture for Underwater Image Enhancement

https://github.com/weixin-liang/mixture-of-mamba

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Mixture-of-Mamba: Enhancing Multi-Modal State-Space Models with Modality-Aware Sparsity

https://github.com/wenbowen123/icra20-hand-object-pose

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Robust, Occlusion-aware Pose Estimation for Objects Grasped by Adaptive Hands

https://github.com/wenchaozheng/wrf-gsplus

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Neural Representation for Wireless Radiation Field Reconstruction: A 3D Gaussian Splatting Approach

https://github.com/wenjuan7275/matir

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MatIR: A Hybrid Mamba-Transformer Image Restoration Model

https://github.com/wenlinyao/hdflow

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HDFlow: Enhancing LLM Complex Problem-Solving with Hybrid Thinking and Dynamic Workflows

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