Papers with Code 아카이브

Computational Efficiency

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 1
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/shinjaehyeok/e_detector_paper

공식 코드

E-detectors: a nonparametric framework for sequential change detection

https://github.com/shivmgg/crisp

공식 코드

CRISP: Hybrid Structured Sparsity for Class-aware Model Pruning

https://github.com/shixinxing/nngpvae-official

공식 코드

Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling

https://github.com/shuai-huang/1Bit-CS

공식 코드

Approximate Message Passing with Parameter Estimation for Heavily Quantized Measurements

https://github.com/shufangxun/llava-mod

공식 코드

LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

https://github.com/shwai-he/meo

공식 코드

Merging Experts into One: Improving Computational Efficiency of Mixture of Experts

https://github.com/simnibs/dipole-fit

공식 코드

Electric Field Models of Transcranial Magnetic Stimulation Coils with Arbitrary Geometries: Reconstruction from Incomplete Magnetic Field Measurements

https://github.com/simontindemans/TCLcontrol

공식 코드

Low-complexity decentralized algorithm for aggregate load control of thermostatic loads

https://github.com/sirmarcel/gknet-archive

공식 코드

Heat flux for semi-local machine-learning potentials

https://github.com/siyisun99/imagic-500_benchmark

공식 코드

IMAGIC-500: IMputation benchmark on A Generative Imaginary Country (500k samples)

https://github.com/siyiwu0330/SDF-TopoNet

공식 코드

SDF-TopoNet: A Two-Stage Framework for Tubular Structure Segmentation via SDF Pre-training and Topology-Aware Fine-Tuning

https://github.com/sjladams/bnn_dp

공식 코드

BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming

https://github.com/sjtubrian/mm-attack

공식 코드

Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack

https://github.com/sldgroup/emcad

공식 코드

EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation

https://github.com/sleepymalc/miss

공식 코드

Most Influential Subset Selection: Challenges, Promises, and Beyond

https://github.com/slicerdmri/dfc

공식 코드

Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellation

https://github.com/sliu675/autoseqrec

공식 코드

AutoSeqRec: Autoencoder for Efficient Sequential Recommendation

https://github.com/smcch/brain_tumor_detection_ultrasound

공식 코드

Real-Time Brain Tumor Detection in Intraoperative Ultrasound Using YOLO11: From Model Training to Deployment in the Operating Room

https://github.com/smlab-niser/23retinald

공식 코드

Retinal Fundus Multi-Disease Image Classification using Hybrid CNN-Transformer-Ensemble Architectures

https://github.com/snailforce/sim-net

공식 코드

Learning to Manipulate Artistic Images

https://github.com/snap-stanford/distance-encoding

공식 코드

Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning

https://github.com/snu-adsl/bbea

공식 코드

B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Search

https://github.com/sobhanhemati/Efficient-Spectral-Hashing-ESH-

공식 코드

A non-alternating graph hashing algorithm for large scale image search

https://github.com/soistesimmer/fetch

공식 코드

Don't Get Lost in the Trees: Streamlining LLM Reasoning by Overcoming Tree Search Exploration Pitfalls

https://github.com/songc0a/fast-gpr-fwi

공식 코드

Fast ground penetrating radar dual-parameter full waveform inversion method accelerated by hybrid compilation of CUDA kernel function and PyTorch

https://github.com/sony/soundctm

공식 코드

SoundCTM: Unifying Score-based and Consistency Models for Full-band Text-to-Sound Generation

https://github.com/sonyresearch/simba

공식 코드

SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

https://github.com/spa-junghokim/protoocc

공식 코드

ProtoOcc: Accurate, Efficient 3D Occupancy Prediction Using Dual Branch Encoder-Prototype Query Decoder

https://github.com/speedinghzl/CCNet

공식 코드

CCNet: Criss-Cross Attention for Semantic Segmentation

https://github.com/squareroot3/gromov-wasserstein-for-graph

공식 코드

A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data

https://github.com/sspring137/EagleEye

공식 코드

Detecting Localized Density Anomalies in Multivariate Data via Coin-Flip Statistics

https://github.com/stanford-futuredata/selection-via-proxy

공식 코드

Selection via Proxy: Efficient Data Selection for Deep Learning

https://github.com/stanfordasl/rl4amod

공식 코드

Robo-taxi Fleet Coordination at Scale via Reinforcement Learning

https://github.com/stanfordasl/rompc

공식 코드

Linear Reduced Order Model Predictive Control

https://github.com/stanfordmimi/medvae

공식 코드

MedVAE: Efficient Automated Interpretation of Medical Images with Large-Scale Generalizable Autoencoders

https://github.com/stanifrolov/spotdiffusion

공식 코드

SpotDiffusion: A Fast Approach For Seamless Panorama Generation Over Time

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