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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/state-spaces/mamba

공식 코드

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

https://github.com/stellacydong/Integrating-Generative-Models-and-Reinforcement-Learning-for-Reinsurance-Optimization

공식 코드

A Hybrid Framework for Reinsurance Optimization: Integrating Generative Models and Reinforcement Learning

https://github.com/steven-ccq/vilamp

공식 코드

Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation

https://github.com/stutipathak5/gps-for-point-clouds

공식 코드

GP-PCS: One-shot Feature-Preserving Point Cloud Simplification with Gaussian Processes on Riemannian Manifolds

https://github.com/summitgao/WBANet

공식 코드

Wavelet-based Bi-dimensional Aggregation Network for SAR Image Change Detection

https://github.com/summitgao/msfmamba

공식 코드

MSFMamba: Multi-Scale Feature Fusion State Space Model for Multi-Source Remote Sensing Image Classification

https://github.com/sunjin19126/caterpillar

공식 코드

Caterpillar: A Pure-MLP Architecture with Shifted-Pillars-Concatenation

https://github.com/sunpengfei1122/DMU

공식 코드

Delayed Memory Unit: Modelling Temporal Dependency Through Delay Gate

https://github.com/susan571/lensllm

공식 코드

LENSLLM: Unveiling Fine-Tuning Dynamics for LLM Selection

https://github.com/swagshaw/asc-cl

공식 코드

Continual Learning For On-Device Environmental Sound Classification

https://github.com/swiman/mamba-medical-classification

공식 코드

Classification of Gleason Grading in Prostate Cancer Histopathology Images Using Deep Learning Techniques: YOLO, Vision Transformers, and Vision Mamba

https://github.com/switchsyj/adae2ml-xsf

공식 코드

Adaptive End-to-End Metric Learning for Zero-Shot Cross-Domain Slot Filling

https://github.com/syanng/blazeneo

공식 코드

BlazeNeo: Blazing fast polyp segmentation and neoplasm detection

https://github.com/sylvie-x/draglora

공식 코드

DragLoRA: Online Optimization of LoRA Adapters for Drag-based Image Editing in Diffusion Model

https://github.com/sypsyp97/Trainable-Fourier-Series

공식 코드

Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier Series

https://github.com/szrlee/GPT-HyperAgent

공식 코드

Scalable Exploration via Ensemble++

https://github.com/szrlee/ensemble_plus_plus

공식 코드

Scalable Exploration via Ensemble++

https://github.com/taeheejeon22/morphsubdecomp-korean

공식 코드

Improving Korean NLP Tasks with Linguistically Informed Subword Tokenization and Sub-character Decomposition

https://github.com/takeuchi-lab/Learning-Interpretable-Metric-between-Graphs

공식 코드

Distance Metric Learning for Graph Structured Data

https://github.com/tanmdl/watt-effnet

공식 코드

WATT-EffNet: A Lightweight and Accurate Model for Classifying Aerial Disaster Images

https://github.com/tarps-group/taddaa

공식 코드

A Targeted Accuracy Diagnostic for Variational Approximations

https://github.com/tavrnn/tavrnn

공식 코드

Graph-Based Representation Learning of Neuronal Dynamics and Behavior

https://github.com/techmonsterwang/illama

공식 코드

Adapting LLaMA Decoder to Vision Transformer

https://github.com/tejasanvekar/gpr-net

공식 코드

GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning

https://github.com/tensorflow/models

공식 코드

MoViNets: Mobile Video Networks for Efficient Video Recognition

https://github.com/teslatasy/popos

공식 코드

POPoS: Improving Efficient and Robust Facial Landmark Detection with Parallel Optimal Position Search

https://github.com/tfwang-9527/gs-3i

공식 코드

GS-I$^{3}$: Gaussian Splatting for Surface Reconstruction from Illumination-Inconsistent Images

https://github.com/tgrex6/unetvl

공식 코드

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM

https://github.com/thaipduong/LieFVIN

공식 코드

Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems

https://github.com/thanhnguyentang/neural-offline-rl

공식 코드

VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation

https://github.com/thecml/baysurv

공식 코드

Efficient Training of Probabilistic Neural Networks for Survival Analysis

https://github.com/thensib/repvgg-gelan

공식 코드

RepVGG-GELAN: Enhanced GELAN with VGG-STYLE ConvNets for Brain Tumour Detection

https://github.com/theundercover01/caga-a-cascaded-dilated-convolution-approach-for-mpox-lesion-classification

공식 코드

A Cascaded Dilated Convolution Approach for Mpox Lesion Classification

https://github.com/theziqi/dccc

공식 코드

Dynamic Clustering and Cluster Contrastive Learning for Unsupervised Person Re-identification

https://github.com/thinkxca/3dgs

공식 코드

3D Gaussian Splatting against Moving Objects for High-Fidelity Street Scene Reconstruction

https://github.com/thqiu0419/mlwnet

공식 코드

Efficient Multi-scale Network with Learnable Discrete Wavelet Transform for Blind Motion Deblurring

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