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/uclnlp/APE

공식 코드

Training Adaptive Computation for Open-Domain Question Answering with Computational Constraints

https://github.com/uclnlp/emat

공식 코드

An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks

https://github.com/ucr-robotics/ced_detector

공식 코드

Centroid Distance Keypoint Detector for Colored Point Clouds

https://github.com/udc-gac/venom

공식 코드

VENOM: A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores

https://github.com/uestc-liuzq/LightTR

공식 코드

LightTR: A Lightweight Framework for Federated Trajectory Recovery

https://github.com/uiuctml/OTCPCC

공식 코드

Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport

https://github.com/umutsimsekli/sgd_first_exit_time

공식 코드

First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise

https://github.com/unites-lab/occult

공식 코드

Occult: Optimizing Collaborative Communication across Experts for Accelerated Parallel MoE Training and Inference

https://github.com/uoguelph-mlrg/ggm-metrics

공식 코드

On Evaluation Metrics for Graph Generative Models

https://github.com/ur-whitelab/mol.dev

공식 코드

Predicting small molecules solubilities on endpoint devices using deep ensemble neural networks

https://github.com/usail-hkust/CoLLMLight

공식 코드

CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal Control

https://github.com/usef-kh/fer

공식 코드

Facial Emotion Recognition: State of the Art Performance on FER2013

https://github.com/ustc-hyin/ClearSight

공식 코드

ClearSight: Visual Signal Enhancement for Object Hallucination Mitigation in Multimodal Large language Models

https://github.com/ustguy/flare23

공식 코드

Iterative Semi-Supervised Learning for Abdominal Organs and Tumor Segmentation

https://github.com/utiasSTARS/dpc-net

공식 코드

DPC-Net: Deep Pose Correction for Visual Localization

https://github.com/utiasdsl/fmpc_socp

공식 코드

Differentially Flat Learning-based Model Predictive Control Using a Stability, State, and Input Constraining Safety Filter

https://github.com/val-iisc/dajat

공식 코드

Efficient and Effective Augmentation Strategy for Adversarial Training

https://github.com/valeriobelcamino/unipa_inner_speech

공식 코드

A Social Robot with Inner Speech for Dietary Guidance

https://github.com/vectozavr/thanos

공식 코드

Thanos: A Block-wise Pruning Algorithm for Efficient Large Language Model Compression

https://github.com/vero1925/FocusTrack

공식 코드

FocusTrack: A Self-Adaptive Local Sampling Algorithm for Efficient Anti-UAV Tracking

https://github.com/versestech/cavi-cmn

공식 코드

Gradient-free variational learning with conditional mixture networks

https://github.com/vhmedina/deepcure

공식 코드

The Deep Promotion Time Cure Model

https://github.com/vict0rsch/PhAST

공식 코드

PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design

https://github.com/viharoszsolt/idenas

공식 코드

Model Input-Output Configuration Search with Embedded Feature Selection for Sensor Time-series and Image Classification

https://github.com/vik0/LangevinDQN

공식 코드

https://github.com/vinairesearch/lfm

공식 코드

Flow Matching in Latent Space

https://github.com/vineetjain96/merlin

공식 코드

Learning to Reach Goals via Diffusion

https://github.com/vinh-tr-hoang/doeviapace

공식 코드

Scalable method for Bayesian experimental design without integrating over posterior distribution

https://github.com/vinloo/u-net-receptive-field-study

공식 코드

Demystifying the Effect of Receptive Field Size in U-Net Models for Medical Image Segmentation

https://github.com/vinusankars/beast

공식 코드

Fast Adversarial Attacks on Language Models In One GPU Minute

https://github.com/vinyehshaw/hff

공식 코드

Rethinking Brain Tumor Segmentation from the Frequency Domain Perspective

https://github.com/viptankz/btr

공식 코드

Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC

https://github.com/virobo-15/gmnr

공식 코드

Generative Multiplane Neural Radiance for 3D-Aware Image Generation

https://github.com/vis-opt-group/sci

공식 코드

Toward Fast, Flexible, and Robust Low-Light Image Enhancement

https://github.com/vis-sustech/paretotracker

공식 코드

ParetoTracker: Understanding Population Dynamics in Multi-objective Evolutionary Algorithms through Visual Analytics

https://github.com/viscloud/ff

공식 코드

Scaling Video Analytics on Constrained Edge Nodes

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